Senior AI/ML + Full-Stack Engineer

Important Note

We are seeking experienced, high-caliber professionals with a proven track record at top-tier technology companies (FAANG, leading startups, or enterprise AI teams). This role requires deep technical expertise and hands-on experience building production-grade AI systems. We conduct rigorous technical interviews and thorough background checks. If you do not have relevant experience or cannot confidently demonstrate your capabilities, please do not apply.

About Us

We're filling a role for a client - a nimble mid-market firm building an in-house AI platform to transform how we leverage data to make better decisions as well as achieve operational efficiency. Our goal: leverage multi-agent orchestration, retrieval-augmented generation (RAG), MCP, and advanced evaluation frameworks to deliver trusted, auditable insights at scale. If you thrive on shaping architecture and care deeply about model performance and reliability, this is your chance to make big decisions in a fast-moving environment.

What You'll Do

• Architect Multi-Agent Systems:
  Design and implement orchestration patterns for LLM agents and tool integrations, ensuring robust handoffs and context management.
• Build Retrieval-Augmented Workflows:
  Define strategies for document chunking, embeddings, and retrieval diagnostics to maximize precision, recall, and groundedness.
• Develop Evaluation Frameworks:
  Create offline and online evaluation harnesses for precision, recall, F1 score, consistency, and latency. Integrate golden datasets and adversarial tests into CI/CD pipelines.
• Data Strategy & Quality:
  Lead dataset curation and labeling workflows; propose prompt optimizations, fine-tuning or parameter-efficient approaches where justified.
• Implement Guardrails:
  Design defenses against prompt injection and enforce output validation for compliance and trust.
• Observability & LLMOps:
  Instrument dashboards for model metrics, retrieval quality, and cost/latency tracking. Establish versioning and lineage for prompts, datasets, and configurations.
• End-to-End Development:
  Build and deploy web applications, APIs, and dashboards for AI workflows.
• Cloud Infrastructure:
  Design and manage cloud-native environments (AWS/GCP/Azure), including containerization (Docker/Kubernetes) and CI/CD pipelines.
• Frontend & Backend:
  Implement user interfaces (React, Vue, or similar) and backend services (Python/FastAPI, ) for AI integration.
• Mentor & Multiply:
  Guide our in-house engineers, set standards, and deliver durable architectural documentation.

You'll Excel If You Have

• 8+ years
  in applied ML/AI systems, including production-grade LLM or multi-agent architectures.
• Experience at top-tier tech companies (FAANG, equivalent startups, or enterprise AI teams) delivering production-grade AI systems.
• Proven experience with
  RAG systems
  , evaluation design, and improving precision/recall/F1 in real-world deployments.
• Hands-on experience with LangChain, LlamaIndex, MCP, and orchestration frameworks for multi-agent systems.
• Expertise in designing
  evaluation datasets
  , adversarial tests, and regression suites.
• Full-Stack Expertise
  : Strong proficiency in modern frontend frameworks (React, Angular, or Vue) and backend development (Python, ).
• Cloud & DevOps: Hands-on experience with AWS/Azure/GCP, container orchestration (Kubernetes), and infrastructure-as-code (Terraform/CDK).
• API Design: Ability to build RESTful and GraphQL APIs for AI services.

Nice-to-Haves

• Experience in financial modeling (e.g. converting Excel financial models to Python)
• Familiarity with compliance frameworks (e.g., SOC 2) and model risk governance.
• Background in fine-tuning strategies and human-in-the-loop labeling.
• Startup for entrepreneurial experience.

Why Join Us

• High Ownership:
  Drive architecture and standards for a mission-critical AI platform while leading other engineers.
• Startup Agility:
  Move fast, make decisions, and see direct business impact.
• Strategic Domain:
  Work on problems where trust and accuracy matter most.

Contract Details

• Duration:
  6 months (extendable)
• Engagement:
  Full-time (40 hrs/week)
• Start Date:
  ASAP
• Compensation:
  Target $15k-$17k/mo based on experience

How to Apply

• Send your resume, portfolio/GitHub, and a short write-up on a production AI system you improved (include metrics like precision, recall, F1, and groundedness).