DATA & AI STAFFING
SAN FRANCISCO

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Lead AI Engineer
Location: San Francisco Bay Area | Hybrid
Salary: $250-300k + Equity

Join a well-funded, AI-native startup at the forefront of redefining how digital products are designed and shipped.

This team is building a next-generation design platform where every screen is real, production-ready code. Designers work directly in the medium that ships, not static mockups, with AI deeply embedded into the workflow to accelerate iteration while preserving precision, consistency, and control.

Backed by top-tier Bay Area investors and senior product leaders from companies including Shopify, Notion, Dropbox, Stripe, and OpenAI, the company has strong runway, a high bar for talent, and ambitious plans ahead.

They’re now hiring their first dedicated Lead AI Engineer to own the model layer and drive AI performance across the product.

The Opportunity

You’ll work directly with the CTO and founding team to define and execute the AI strategy at the model level.

This is a hands-on, production-focused AI engineering role centered on:

• Fine-tuning LLMs for real-world use cases
• Optimizing inference speed, cost, and reliability
• Designing and deploying custom Small Language Models (SLMs)
• Establishing evaluation, benchmarking, and observability standards

What You’ll Be Responsible For

Fine-Tuning & Model Strategy

• Own fine-tuning workflows (LoRA, adapters, distillation, full fine-tuning)
• Decide when to fine-tune vs optimize at the system or prompt level
• Iterate models based on production feedback
• Balance quality, latency, and cost tradeoffs

Model Optimization & Performance

• Improve inference speed and throughput
• Reduce cost per request
• Enhance reliability and output consistency
• Define model evaluation and benchmarking frameworks

Custom SLM Development

• Design and train custom SLMs for specific design-to-code workflows
• Identify when smaller models outperform larger ones
• Deploy and maintain real-time, streaming AI systems
• Support multi-step and agentic AI capabilities within the product

What They’re Looking For

• 5+ years of software engineering experience
• 2+ years building with LLMs in production environments
• Proven hands-on fine-tuning experience (LoRA, distillation, adapters, etc.)
• Experience deploying custom or specialized models
• Strong intuition around inference tradeoffs: latency, throughput, cost, reliability
• Proficiency in Python and TypeScript / Node.js

Nice to have:

• ONNX runtime or model optimization tooling
• Experience with orchestration frameworks (e.g., LangChain)
• WebSockets, Redis, or real-time streaming systems
• Background in AI-native or code-generation products
• A PhD or advanced degree is welcomed, but demonstrated production impact is the priority.

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AI Engineer
San Francisco, California

Remote

$200,000 – $220,000 + Equity

About the Company

This innovative health tech startup is working to improve the oncology drug development process by providing better patient data to drug developers as well as better access to clinical trials for patients. This series B startup is expending to meet demand.

About the Role

As an AI Engineer, you will design and deliver applied AI systems (LLMs/CV/multimodal) that automate clinical variable abstraction and clinical note generation-with repeatable validation, robust documentation, and HITL feedback loops. Heavy emphasis on data engineering and backend rigor to make models usable and efficient.

Role Responsibilities

• Build models and pipelines across EMR/EHR, imaging, clinical reports
• Translate ambiguous clinical requirements into measurable ML objectives
• Define metrics, design experiments, estimate error; review peer work
• Deliver validated AI components for abstraction/note generation; meaningfully reduce manual QA workload via HITL; standardize documentation/testing; establish performant data manipulation patterns (e.g., PySpark, SQL/Postgres) that speed iteration.

Key Requirements

• Python
• Pytorch or Tensorflow
• Data engineering: PySpark, SQL, Postgres, query tuning, data modeling
• Cloud data platforms (e.g., Databricks, S3/Snowflake/Azure/GCP)
• Nice to have experience in oncology/biotech/health tech

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Senior AI Engineer

San Francisco or New York · Up to $300k base + significant performance bonus · In-person · No sponsorship

I’m working on a rare and genuinely compelling search with a leading global investment firm. They’re building an internal AI function from the ground up – a small, high-impact team embedded directly within the investment organisation – with a mandate to reimagine how investment work gets done using AI.

This is not a side project or an innovation lab. The firm has operated using the same Excel, PowerPoint, and email workflows for 25+ years and has made a deliberate decision to change that. You’ll be identifying the repetitive, high-volume analytical work happening across the firm and building the agentic systems that automate and augment it – working directly alongside experienced investment professionals every day.

The culture is flat, entrepreneurial, and deeply technical. These are smart people who take a meritocratic approach and trust their team to manage their own work. If you want proximity to senior decision-makers and real influence over how a firm at this level operates, there aren’t many roles like it.

What you’ll be doing:

• Design and build the technical architecture for an AI-powered investment platform, including agentic workflows, RAG systems, and LLM-based tooling
• Identify repetitive analytical and operational tasks across the firm and build production-grade systems to automate them
• Integrate LLMs into real investment workflows – connecting AWS, Snowflake, Salesforce, and external data sources
• Build evaluation frameworks to ensure AI output meets institutional-grade standards
• Make build-vs-buy recommendations on AI vendors, platforms, and infrastructure
• Work directly with investment partners and operators, translating complex processes into AI-enabled solutions
• Provide technical direction and mentorship as the team grows

What my client is looking for:

• 5-8 years of software engineering experience, with a deliberate recent pivot into AI/GenAI applications
• Production experience with LLM applications, RAG systems, and agentic frameworks
• Strong Python and cloud infrastructure (AWS preferred)
• Solid software engineering fundamentals – architecture, distributed systems, CI/CD
• Product intuition for AI systems and good judgment on when and how to apply AI effectively
• Comfortable switching between highly technical conversations and discussions with non-technical senior stakeholders
• Entrepreneurial mindset – startup background (Series A-C) is ideal
• Curiosity about investment workflows; prior financial services experience is a plus but not required

Stack includes AWS, Snowflake, Claude, Claude Code, ChatGPT, and Fivetran.

US citizens and GC holders only – no sponsorship available now or in the future.

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Senior AI Engineer – Bay Area – $200k-$250k base + RSUs · Hybrid (Tues-Thurs onsite)

I’m partnering with a fast-growing Series C SaaS company on what is genuinely one of the more exciting AI engineering roles I’ve worked on this year. They’ve hit significant scale, built a strong market position, and are now entering a new chapter – with AI at the centre of everything they’re building next.

This is a production-first role. You won’t be running experiments or building proofs of concept – you’ll be designing and shipping agentic AI systems that automate complex, high-stakes enterprise workflows, replacing weeks of manual effort with intelligent, reliable automation at scale. The impact is immediate and highly visible.

You’ll be joining a collaborative AI team of around 14, with strong alignment to the product and engineering leadership. The culture values curiosity, ownership, and people who challenge ideas – this is a place where strong engineers have real influence over what gets built and how.

What you’ll be doing:

• Design and build LLM-powered agentic systems with multi-step reasoning, evidence grounding, and decision support
• Develop RAG pipelines, vector search, and document parsing and classification systems
• Build and own distributed AI pipelines and long-running agentic workflows using Temporal
• Architect production-grade LLM and retrieval systems, optimising for latency, cost, and reliability
• Embed guardrails, human-in-the-loop workflows, and evaluation pipelines to ensure trustworthy AI outputs
• Partner closely with product and engineering to bring cutting-edge AI from concept to production
• Help set the technical bar for how the team builds with modern LLMs – your decisions shape what ships

What they’re looking for:

• 7+ years of software engineering experience, with 2+ years working directly in AI/ML engineering
• Proven track record shipping production LLM applications – RAG pipelines, agent frameworks, and evaluation systems
• Strong Python; TypeScript is a bonus
• Hands-on experience with vector databases (Pinecone, Chroma, FAISS) and embedding systems
• Comfortable reasoning about distributed systems and decomposing complex problems into agentic workflows
• Startup background is important – they want builders who take full ownership, not order-takers
• Curious, collaborative, and energised by ambiguity rather than unsettled by it

Stack includes AWS Bedrock, Python, Temporal, Snowflake, and vector DB/RAG systems. US citizens and GC holders preferred; exceptional H1B candidates will be considered.

If you’ve spent your career building real AI systems – not demos – and you’re looking for a role where your work genuinely moves the needle for thousands of enterprise customers, this is worth a conversation.

Senior AI Engineer – Bay Area – $200k-$250k base + RSUs · Hybrid (Tues-Thurs onsite)

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Principal AI Engineer

San Francisco, CA – 4 days onsite

$225,000 – $250,000 + bonus + LTI; $500,000-$700,000 total

THE COMPANY

Harnham is partnering with a top financial services company in the NYC area, which is looking for an experienced AI / ML Engineer. This person will be at the forefront of building AI automation applications for new ways at identifying cost-saving opportunities. You’ll partner with executive teams across the company and own generative AI, LLM and reinforcement learning modeling and deployment.

RESPONSIBILITIES

• Work closely with department heads to align on business goals, define machine learning challenges, and design effective ML solutions.
• Develop and deploy machine learning models, including building data pipelines, orchestrating ML workflows, and optimizing system performance and reliability.
• Maintain a robust codebase by writing well-tested code, covering both functional and non-functional aspects such as unit, integration, and load testing.
• Stay informed on industry trends and advancements in generative AI, LLMs, agentic AI, deep learning, experiment with new model concepts, and run both offline and online evaluations.
• Actively share knowledge through internal presentations, tech talks, and by promoting best practices in engineering and technology use.

SKILLS AND EXPERIENCE

• Advanced degree (Master’s or PhD) in Computer Science, Machine Learning or a related field.
• Over 7 years of hands-on experience developing and deploying production-ready machine learning / deep learning / AI systems, covering the full model lifecycle-training, tuning, deployment, serving, and monitoring.
• Enterprise-level application experience, ideally in real-time preferred.
• Expertise in cloud infrastructure (especially AWS), machine learning orchestration tools like Kubeflow, TensorFlow, and the use of Feature Stores in live environments.
• Experience as a tech-lead for scaling MLE teams preferred.
• Commercial experience combination of big tech and scaling startups / scrappy environments a plus.

BENEFITS

The compensation package contains a base salary, bonus, LTI and a comprehensive benefits package.

HOW TO APPLY

Please register your interest by sending your CV via the Apply link on this page.

KEY TERMS

Artificial Intelligence | Generative AI | GenAI | Machine Learning | ML Engineer | Engineering | Deployment | Production | Real Time | Enterprise | Statistics | Mathematics | Financial Services | Banking | Python | Anomaly Detection | Fintech | Agentic AI | AI Agents

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Senior AI Engineer

Locations: San Francisco, CA Work Arrangement: 4-5 days per week onsite (In-person collaboration focus) Compensation: $425,000 – $600,000 Total Cash (Base + ~50% Performance Bonus)

The Opportunity

Our client is a premier global technology investment firm with a 26-year track record of excellence and over 200 employees. Despite their scale, they maintain a flat, entrepreneurial, and “deeply technical” culture.

They are currently seeking a Senior AI Engineer(VP Level) to help lead a digital transformation. This is not a “maintenance” role; you will be tasked with reimagining the future of private equity. You will build the AI agents and autonomous workflows that will automate and augment the high-volume analytical work currently performed by investment professionals.

Note: This role does not support sponsorship’s

The Mission

Your goal is to move the firm beyond legacy workflows (Excel, email, and PowerPoint) and toward an AI-augmented investment process.

• Focus: Building production-grade agentic systems and AI applications that drive business value.

• Philosophy: Our client is not training foundational models from scratch. Instead, you will use off-the-shelf models (OpenAI, Anthropic, etc.) and focus on sophisticated orchestration, RAG systems, and workflow integration.

• Impact: You will identify repetitive, associate-level tasks and build systems where AI performs 80% of the heavy lifting, allowing humans to focus on high-level refining and decision-making.

Key Responsibilities

• Architect & Build: Design and deploy AI-powered systems and agent-based frameworks into production.

• Integrate: Develop the architecture to connect LLMs with diverse data sources, including AWS, Snowflake, Salesforce, and external alternative datasets (market research, web traffic, etc.).

• Collaborate: Work directly with Investment Partners and Operating Teams to translate complex investment processes into automated AI workflows.

• Innovate: Serve as a technical leader in deciding when to use single vs. multi-agent systems and selecting the appropriate LLM for specific use cases.

Candidate Profile

We are looking for a builder, not a maintainer. The ideal candidate likely comes from a high-growth startup environment (Series A-C) or a specialized internal product team.

Technical Requirements

• Foundation: 5-10 years of professional experience, including at least 4+ years of core software engineering.

• AI Pivot: A deliberate focus over the last 2-4 years on Generative AI and LLM application design.

• Stack: Mastery of Python and Cloud Infrastructure (AWS preferred).

• Data Savvy: Experience with Snowflake and modern data pipelines (Fivetran, etc.). Exposure to financial data (EBITDA, market data) is a significant plus.

Soft Skills & Mindset

• Entrepreneurial: You thrive in a flat organization where you are expected to take ownership and manage your own work.

• “Code-Switcher”: Ability to communicate technical architecture to engineers while explaining business value to Senior Investment Partners.

• Practicality: You prioritize shipping functional, high-impact tools over theoretical or academic exercises.

Why Join?

• High Visibility: This role is integrated into the investment team; you will interact with firm leadership daily.

• Modern Tools: The team is already leveraging AI-assisted coding (Claude Code) and modern data stacks to move fast.

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Senior AI Engineer | Series C GRC Startup | San Francisco (Hybrid)

Location: San Francisco, CA (Hybrid – 3 days/week in office)

Compensation: $200,000 – $250,000 base salary + significant equity

The Role

This is a high-impact, high-ownership position. The selected candidate will serve as the technical authority on how the team designs, ships, and continuously improves AI in production. From LLM pipelines and RAG architectures to agentic workflows and human-in-the-loop systems, this engineer will work across the full stack of modern AI infrastructure alongside a team that takes engineering craft seriously.

What You’ll Do

• Design, build, and own production AI systems end-to-end, including LLM pipelines, retrieval-augmented generation (RAG), reranking, vector stores, and orchestration
• Architect scalable LLM + retrieval + agent systems that operate reliably in enterprise production environments
• Build and maintain human-in-the-loop (HITL) workflows that keep domain experts meaningfully in the decision process
• Develop evaluation frameworks and apply quantitative analysis to systematically measure and improve AI system performance
• Partner with product and engineering leadership to shape the AI roadmap and define best practices across the team
• Set architectural standards that influence how the broader organization builds and ships AI

Required:

• 10+ years of software engineering experience, including 3+ years working directly on ML/AI systems in production (or 6+ YOE for Senior level)
• Deep hands-on experience with RAG, embeddings, reranking, and vector databases (Pinecone, FAISS, Chroma, or similar)
• Proven experience building agentic workflows and multi-step LLM pipelines
• Strong proficiency in Python and TypeScript
• Experience designing and implementing AI evaluation frameworks using quantitative methods

Nice to Have:

• Background in compliance, security, or other regulated enterprise domains (GRC experience is a strong plus)
• Familiarity with enterprise data platforms or Snowflake-based analytics
• Experience with orchestration systems like Temporal or Airflow
• Hands-on experience with LLM evaluation platforms such as Braintrust

Compensation and Benefits

• $200,000 – $250,000 base salary + significant equity at Series C
• Employer-paid health, dental, and vision coverage for the employee and dependents
• 401(k) with company match
• Hybrid flexibility with a collaborative SF home base

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Senior AI Engineer (Agentic Systems & LLM Applications)
San Francisco, CA (Hybrid) Tuesday – Thursday (Onsite)
$180,000 – $220,000 base + equity + benefits

About the Company

This organization builds software that helps businesses operate with greater transparency, accountability, and trust. Its platform supports critical workflows around governance, risk, and operational decision-making, enabling teams to manage complex processes with speed and confidence.

The company has reached meaningful scale and is now investing heavily in its next phase – embedding advanced AI directly into core product workflows. This is not an experimentation layer; these are production systems that customers rely on to make real decisions.

Engineering teams operate with high ownership and low overhead. The environment rewards people who take initiative, challenge assumptions, and deliver systems that work in the real world.

About the Role

This is a high-ownership, builder role for engineers who want to push beyond “feature-level AI” and design systems that actually reason, act, and operate in production.

You will own end-to-end development of AI systems – from architecture and design through deployment, evaluation, and iteration. The focus is on building agentic systems and retrieval-driven pipelines that can handle complex, multi-step workflows across large volumes of structured and unstructured data.

This role is best suited for engineers who have already shipped LLM-based systems and want to go deeper – improving system reliability, designing evaluation frameworks, and building AI that can be trusted in high-stakes environments.

You’ll work closely with product and engineering leadership to define what gets built, not just how it gets built.

Key Responsibilities

• Architect and deploy production LLM systems capable of multi-step reasoning and decision support
• Build and scale agentic workflows that automate complex, long-running processes
• Design end-to-end RAG pipelines (ingestion, embeddings, retrieval, ranking, generation)
• Develop evaluation frameworks and guardrails to ensure system accuracy, reliability, and safety
• Optimize systems for latency, cost efficiency, and production performance
• Partner with product and engineering leaders to identify and prioritize high-impact AI opportunities
• Contribute to backend systems and infrastructure supporting large-scale AI deployment

Must Haves

• 7+ years of software engineering experience, including 2+ years building AI/ML systems
• Strong Python expertise and experience building production-grade systems
• Proven track record shipping LLM-based applications into production
• Hands-on experience with RAG pipelines, embeddings, and vector databases
• Experience building agent-based or multi-step AI systems
• Strong system design skills with experience in distributed systems
• Clear ownership of systems from initial concept through production and iteration

Nice to Have

• Experience with workflow orchestration or distributed task systems
• Familiarity with backend systems or TypeScript-based services
• Experience working with document-heavy or high-complexity datasets
• Exposure to evaluation frameworks, monitoring systems, or AI safety practices

Why Join

• Build AI systems that operate in real-world, high-stakes environments – not prototypes
• Own the architecture and evolution of agentic systems used by real customers
• Work on problems where correctness, reliability, and trust actually matter
• High autonomy with direct influence on product direction and technical strategy
• Strong compensation, meaningful equity, and comprehensive benefits
• In-person collaboration Tuesday-Thursday with a focused, high-caliber engineering team
• Opportunity to raise the technical bar alongside engineers who have shipped real systems

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