SAN FRANCISCO

AI Engineer Recruitment

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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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Staff Applied AI Engineer | Bay Area (Hybrid) | $200k-$298k base + equity

I’m partnering with a high-growth SaaS company at the cutting edge of AI and compliance on a senior Applied AI Engineer hire.

This is not a typical “build a model and ship it” role.

This is where you define what good AI looks like – owning how systems retrieve, reason, and deliver trustworthy outputs at scale.

You’ll sit at the intersection of research and real-world impact, shaping the intelligence behind core product features.

‘ :

* Improving RAG systems – retrieval quality, chunking, embeddings, hybrid search

* Designing evaluation frameworks (metrics, golden datasets, regression detection)

* Building and tuning ranking + reranking systems (cross-encoders, LLM rerankers)

* Running experiments to validate what actually improves performance

* Debugging failure modes across retrieval, reasoning, and generation

* Prototyping agent-style workflows over complex, document-heavy data

* Exploring ML approaches beyond GenAI (ranking, classification, probabilistic models)

‘ :

* 8-10+ years in applied ML, data science, or AI research

* Strong experience in information retrieval / search relevance

* Hands-on with RAG systems and retrieval optimization

* Deep understanding of evaluation + experimentation (A/B testing, metrics)

* Python + strong problem-solving / research mindset

* Someone who can explain why systems work (or don’t) – not just build them

:

* You’ve only used LLM APIs without optimizing retrieval or evaluation

* Your experience is purely prompt engineering

* You prefer purely academic research without product impact

* You’re looking for a heavily structured, slow-moving environment

Candidates must be based in the Bay Area and open to a hybrid setup.

If you’re interested in making AI systems measurably better – not just building them, drop me a message or comment below.

Happy to share more details confidentially.

#AIJobs #MachineLearning #RAG #SearchRelevance #LLMs #Hiring #BayAreaJobs #TechJobs

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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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AI Engineer / Data Engineer (AI Applications & Investment Systems)

Location & Work Environment

• Strong preference for onsite collaboration (4-5 days/week initially)
• Flexible hybrid approach over time, but not a minimal in-office model
• Culture built on trust, ownership, and autonomy – no rigid policies
• Emphasis on:
• Collaboration
• Knowledge sharing
• High-impact problem solving

About the Role

We are building a next-generation data and AI platform to transform how complex business and investment decisions are made.

This role focuses on reimagining traditional workflows using AI, replacing legacy processes built on spreadsheets, slide decks, and manual analysis with intelligent, automated systems.

You will play a critical role in:

• Designing AI-powered workflows
• Building agent-based systems
• Enabling teams to leverage large-scale, fragmented datasets
• Delivering production-grade AI applications

What You’ll Do

• Design and build AI-powered systems to automate and enhance workflows
• Develop and deploy LLM-based applications and agent frameworks
• Translate complex business processes into scalable AI-driven solutions
• Build and maintain data pipelines and infrastructure
• Integrate data across systems (cloud platforms, data warehouses, APIs)
• Identify repetitive workflows and implement automation at scale
• Partner with cross-functional stakeholders to drive adoption and impact
• Deliver production-ready solutions, not just prototypes

What We’re Looking For

Experience

• 5-8 years of experience (flexible for strong candidates)
• Strong foundation in software engineering
• Recent experience working with Generative AI / LLM applications

Technical Skills

• Proficiency in Python
• Experience with cloud infrastructure (AWS preferred)
• Strong understanding of:
• System design
• Distributed systems
• Data architecture
• Experience building production-grade AI systems

AI / LLM Expertise

• Hands-on experience with:
• RAG (Retrieval-Augmented Generation)
• Agent-based systems
• LLM application design and orchestration
• Ability to:
• Choose appropriate models (OpenAI, Anthropic, etc.)
• Design efficient, scalable AI architectures
• Evaluate tradeoffs (cost, latency, performance)

Data & Technology Stack

• Cloud: AWS
• Data: Snowflake, modern ELT tools (e.g., Fivetran)
• AI tools: LLMs (e.g., Claude, ChatGPT)
• CRM & business systems integrations
• Extensive use of AI-assisted development tools

You will work with a wide range of data sources, including:

• Internal operational data
• Third-party datasets and research
• Market and alternative data (e.g., web, labor, and behavioral signals)

Ideal Candidate Profile

• Strong builder mindset with experience in fast-paced environments
• Background in startups, product teams, or platform engineering
• Deep understanding of both:
• Engineering fundamentals
• Practical AI application design
• Strong product intuition – understands how to apply AI to real problems
• Comfortable making independent decisions in ambiguous environments

Soft Skills

• Entrepreneurial and self-driven
• Strong communicator across technical and non-technical audiences
• Comfortable working with senior stakeholders
• Able to operate with high autonomy and minimal oversight
• Curious, pragmatic, and execution-focused

⏰ Working Style

• Flexible hours; not a strict 9-5 role
• Must be comfortable collaborating across time zones
• Occasional flexibility required for high-priority needs

Compensation & Benefits

• Highly competitive total cash compensation (performance-driven bonus included)
• Comprehensive benefits package:
• Medical, dental, and vision coverage
• Wellness benefits
• Retirement plan (401k)
• Generous PTO

⚡ Interview Process

• Streamlined, fast-moving process
• Focus on:
• Systems thinking
• Practical problem-solving
• AI application design
• No coding tests – emphasis on real-world approach and decision-making

Why This Role?

• Opportunity to transform how complex workflows are done using AI
• Work on high-impact, real-world AI applications
• Operate in a high-autonomy, builder-focused environment
• Be part of a small, elite team driving meaningful innovation

• Seniority Level

  Director

• Industry

  • Staffing and Recruiting

• Employment Type

  Full-time

• Job Functions

  • Finance

• Skills

  • Artificial Intelligence (AI)
  • Engineering
  • Amazon Web Services (AWS)
  • Python (Program

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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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