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Client lead, architect, and senior builder.
$150,000 – $250,000 base plus performance bonus
Remote anywhere in the US. Boston preferred.
On any given engagement you are the technical lead, the architect, a senior builder, the manager of the Malleable engineers staffed with you, and the person who teaches the client's team to take the system over after we roll off.
You are a senior engineer who can lead an architecture conversation with a VP of Engineering on Monday, ship production code midweek, review PRs from your pod, and pair with the client's team on Friday. You do this while running two or three client engagements at a time.
This role suits people who want ownership of outcomes, variety across industries, and a direct hand in shaping how a small AI services firm grows up.
You'll lead engagements, lead engineers, and ship the hard parts yourself.
Own the technical relationship from discovery through handoff: stakeholder workshops, technical roadmap, and delivery against the business outcome.
Each engagement runs with a mix of engineers under your direction, including senior and staff peers. You set architectural direction, run PR review, and keep multiple engagements on track.
Discovery and standups in Slack and Zoom, async PR review, plus 2–3 onsite trips a year for kickoffs and major milestones.
Agent architectures, RAG pipelines, eval frameworks, multi-agent orchestrations. Each one shaped to the client's stack, risk tolerance, and scale.
Python and FastAPI on the backend, React and Next.js on the front end. OpenAI Agents SDK and Claude Agents SDK as the primary agent frameworks.
You write the hard parts yourself (architecture, integrations, core agent logic) and hand the smaller tickets to engineers you are guiding through review.
Frameworks that track model and prompt performance over time as the application, tools, and agents evolve.
MCP servers, custom agent tools, and integrations into client systems like Salesforce, Jira, SAP, internal APIs, and data warehouses.
Pair with their engineers, write the patterns into runbooks, and build internal champions so the system keeps moving after we are gone.
The components, reference architectures, and playbooks you create flow back into our toolkit so the next engagement starts further along.
A senior engineer who has led delivery in client-facing settings and shipped real LLM features.
6+ years building software in production, with at least 2 years in client-facing or senior IC roles where you owned stakeholder relationships.
You have led engineers on shipped projects. You run code reviews that raise the bar, you mentor ICs, and you have good instincts for when to write the code yourself versus hand it off.
Experience with Python and FastAPI on the backend and React and Next.js on the front end.
Production experience with OpenAI Agents SDK or Claude Agents SDK, plus you have built and maintained eval frameworks for production features.
Daily use of Claude Code or Codex. The LLM is part of how you work, not a side experiment.
Strong written and verbal communication, and good product instincts. You can lead a discovery with a CTO, run an exec readout, and turn a vague business problem into a scoped plan with defensible trade-offs.
US Citizen or Permanent Resident. No visa sponsorship now or in the future.
Prior forward-deployed engineer, solutions architect, or consulting engineer experience at a boutique AI shop or top-tier consulting practice.
You have built MCP servers or custom agent tooling, and you have shipped LLM features (GPT, Claude, Gemini) in real enterprise apps beyond chatbot wrappers.
Working familiarity with LangGraph or LangChain and the Vercel AI SDK, with a clear point of view on when to use each.
Cloud experience in AWS, Azure, or GCP, plus Vercel and Supabase. Comfortable with Docker, GitHub Actions, and microservice architectures.
You have shipped on at least one relational database (Postgres, MS SQL Server, MySQL) and one NoSQL store (DynamoDB, Cosmos DB, Firebase).
A track record of teaching or training engineers. Internal enablement programs, bootcamp instruction, conference talks, or technical writing.
Experience defining and tracking post-engagement success metrics: adoption, throughput, cycle time, quality indicators, or business KPIs.
East Coast home base. Our team is on the East Coast, so candidates in or near Boston or New Haven, CT are a plus for working hours overlap and the occasional in-person.
Domain depth in a sector we serve (financial services, property tech, enterprise SaaS, hospitality, professional services).
IaC experience (Terraform), schema migrations, secret management, and secure coding practices.
Open source contributions to agent frameworks, MCP servers, or AI developer tooling.
Founding engineer or early-stage startup experience where you owned 0-to-1 delivery.
You sit alongside the founders, with real influence on hiring, technical direction, and how we run engagements.
You own real outcomes for real clients, not toy demos.
You see a lot of different companies, stacks, and problem shapes in a year, instead of one roadmap.
Short feedback loops, no bureaucracy.
Application review. We read your note, resume, and the AI system link you share.
Intro call. 30 minutes with a co-founder.
Take-home build. A scoped problem you do on your own time. Use any AI tools you want. We expect it.
Live readout. Walk us through what you built, then answer architecture and trade-off questions on the fly without AI assistance.
Final conversation and offer. Closing chat with the founders.
Send a short note covering the items below, plus your resume, LinkedIn, and GitHub, to hiring@malleable.ai.
A link to a working AI system you built (deployment, demo video, or a repo with a README), plus 3–5 sentences on the trickiest architectural call you made and why.
Examples of AI systems you have shipped to production with OpenAI Agents SDK, Claude Agents SDK, or equivalent frameworks.
Any client-facing delivery, consulting, or enterprise rollout experience.
Examples of teaching, training, or enabling other engineers, internally or publicly.
The industries, stacks, and engagement sizes you have worked across.
Your availability and target comp within the range.