Custom Software Engineer

Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Must have skills : Generative AI

Good to have skills : AI Agents & Workflow Integration

Minimum 5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Core Engineering & Day to Day Practice

Strong Python fundamentals

Hands-on experience using Claude Code for day-to-day development and coding workflows

Agentic Systems & Architecture

Proficiency with agentic frameworks (e.g., LangGraph, custom orchestration patterns) — not just chatbot/RAG experience

Experience selecting, integrating, and evaluating LLM APIs (e.g., Anthropic, OpenAI, others), including assessing tradeoffs across models and providers

Proficiency with agentic planning and tool-use patterns (ReAct, Chain-of-Thought + action) experience building and shipping multi-agent pipelines in production, including handling failure modes, loops, and hallucinations

Ability to design prompts systematically as part of end-to-end agent behavior

Comfort with async, event-driven architectures

Memory & Retrieval Architecture

Experience designing agent memory architectures, including short- and long-term memory, embeddings, vector databases, and context window/token management

Experience building and operating production RAG systems, including horizontally scalable vector databases, with attention to latency, reliability, and throughput tradeoffs

Evaluation & Human in the Loop

Ability to define task-specific evals and regression tests to catch prompt drift, retrieval failures, and behavioral regressions

Understanding of online vs. offline evaluation tradeoffs and using results to drive iterative improvements

Experience with human-in-the-loop (HITL) design and evaluation, including approval gating, routing ambiguous outputs to humans, and closing the feedback loop (e.g., Langfuse human annotation evals)

Integration, Governance & Security

Experience with MCP server integration

Experience integrating agents with enterprise systems (internal APIs, identity/auth layers)

Understanding of AI governance: audit trails, explainability, access controls, and data residency constraints

Security-conscious agent design: scoped permissions and prompt injection mitigation

Bonus: Experience operating within IT governance or change management processes