AI Engineer
Our client is a fast-growing physical-AI company building software for complex industrial and manufacturing programs, with an initial focus on shipbuilding. They help engineering, procurement, and production teams turn scattered CAD files, scheduling data, and supply-chain records into one connected model of how a project actually gets built — so that what's learned on one build carries over to the next. The company is lean and fully remote, led by a CTO with two decades of experience in the space, and is currently scaling delivery on a multi-year program with an industrial client. Some of the client's program work carries elevated data-security requirements, which is reflected in the location eligibility below.
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Engagement: Full-time, long-term [ Independent contractor ]
Location: Philippines [Remote]
Working hours: Overlap expected with the client's US Exact hours are confirmed during interviews — this is not a rigid fixed-shift role.
About the Role
On behalf of our client, Second Talent is hiring an AI Engineer. You'll build and ship the client's software using agentic development workflows — taking product requirements, driving coding agents and frameworks to implement against them, verifying the resulting software actually meets the requirements, managing releases, and deploying into the cloud.
What You'll Do
- Build with agents — develop software using agentic coding workflows and frameworks, orchestrating coding agents to implement features across the stack rather than hand-writing every line.
- Build the domain agents — contribute to the client's agent roster (EBOM→MBOM, work packages, scheduling, change-impact, flow advisor, quality, progress-vision), each running graph context → model → write-back with human-in-the-loop gates and an eval-gated prompt registry.
- Own requirements-to-code — understand requirements from the Solutions Lead and product; decompose them; develop/guide agents to implement them correctly.
- Verify quality — write and run evals and tests, review agent output, and catch regressions and hallucinations before release — trust tiers, calibration, no pass, no go.
- Manage releases — own versioning, release management, and change control across the FastAPI API and Celery worker services.
- Deploy to cloud — containerize and ship into the cloud — CI/CD, migrations, environment config, post-deploy verification, observability, and cost-per-build telemetry.
Core Tech Stack (familiarity required)
- Agentic dev: coding-agent workflows & frameworks (e.g., Claude Code / Cursor / agent SDKs; LangGraph, LangChain, CrewAI, DSPy); prompt engineering; evals.
- Backend: Python 3.11, FastAPI, Celery, Pydantic v2, SQLAlchemy 2.x, Alembic.
- Front end: React 18 + TypeScript, TanStack React Query, Tailwind/shadcn UI, Vite.
- AI/models: managed frontier LLMs via a cloud model provider, tiered by capability; RAG, local embeddings, model routing by complexity, eval-gated prompt registry.
- Data: PostgreSQL + pgvector, Neo4j (knowledge graph), object store, Redis; pandas; OR-Tools & networkx (scheduling engine).
- Cloud/delivery: Docker containers, cloud infrastructure, CI/CD, migrations, observability, cost-per-build instrumentation.
Required Qualifications
- 4+ years building and shipping production software, with hands-on experience using AI/agentic tooling to develop and deliver code.
- Full-stack competence across a modern Python + TypeScript stack (FastAPI and/or Node/Express, React).
- Practical experience with LLM application patterns — RAG, agents, tool-calling, and prompt/eval workflows.
- Solid grasp of requirements analysis, testing/evals, release management, and cloud deployment (containers, CI/CD, migrations, environments).
- Comfort in a fast, customer-driven forward-deployed environment, occasionally on-site.
Preferred Qualifications
- Experience with knowledge graphs (Neo4j) and vector retrieval (pgvector).
- Model-serving on a managed cloud provider; local/open-weight models and LoRA fine-tuning.
- Optimization/scheduling (OR-Tools CP-SAT, critical-path methods), PLM/BOM, or planning software.
- Complex, high-mix/low-volume manufacturing or PLM/BOM domain exposure.
Must-Have Skills
Python/FastAPI • TypeScript/React • AI Coding Agents (Claude Code/Cursor/agent SDKs) • LLM Applications (RAG, Agents, Tool-Calling) • Cloud Deployment (Docker, CI/CD) • Testing & Evals • Release Management
