About the Role
We are seeking an experienced Contract AI Engineer with a strong foundation in Software Engineering to join our team.
If you are a seasoned software developer who has successfully transitioned into building, scaling, and deploying AI-driven systems, this role is for you. Rather than focusing purely on research or training models from scratch, you will focus on production-grade integration, performance tuning, robust pipeline engineering, and grounding AI applications into scalable software architectures.
Key Responsibilities
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AI Integration & Application Development: Design and build resilient software systems around LLMs, foundation models, and custom ML components using modern framework architectures (e.g., LangChain, LlamaIndex, Haystack).
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Production Deployment: Transition experimental AI scripts and POCs into reliable, production-grade microservices and API endpoints.
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Vector Search & RAG Systems: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines and vector database integrations (e.g., Pinecone, Qdrant, Milvus, pgvector).
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Software Architecture & Tooling: Apply classical software engineering principles-CI/CD, automated testing, design patterns, clean code, and monitoring-to AI/ML application stacks.
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Model Fine-Tuning & Evaluation: Evaluate model outputs, design prompt templates, implement guardrails/eval frameworks (e.g., Ragas, DeepEval, LangSmith), and fine-tune models where necessary.
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Cross-Functional Engagement: Collaborate closely with product, data engineering, and infrastructure teams to integrate AI deliverables smoothly into our broader ecosystem.
Required Experience & Technical Skills
Core Software Engineering Background
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4+ years of core software development experience (Python, TypeScript/Node.js, Go, or Java).
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Proven track record in building RESTful APIs, microservices, and asynchronous distributed systems.
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Strong practice of standard software methodologies: Unit/Integration Testing, Git workflow, CI/CD, and Docker/Kubernetes.
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Familiarity with cloud providers (AWS, GCP, or Azure).
AI / ML Focus
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1-2+ years hands-on experience integrating AI models and APIs (OpenAI, Anthropic, Hugging Face, Bedrock, Vertex AI) into enterprise applications.
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Solid experience with vector databases and search indexing.
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Experience implementing AI evaluation methods, observability, and cost/latency optimizations.
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Understanding of data handling, ETL pipelines, and API design.
Nice-to-Have Skills
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Experience with agentic frameworks (e.g., AutoGen, CrewAI, LangGraph).
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Familiarity with local model hosting (Ollama, vLLM, TGI).
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Basic experience fine-tuning open-source models (LoRA, QLoRA).
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Background in traditional ML (Scikit-Learn, PyTorch, Pandas) or MLOps practices.
