Description

Key Skills: Python, React, LLM Integration, Vector Databases, Azure, AWS, LangChain, TypeScript, SQL, NoSQL

Good to Have Skills: Enterprise platform integration with Workday HCM or Power Platform, AI governance and compliance-aware development in regulated environments focusing on data privacy in AI models, containerization mastery with Docker and Kubernetes for deploying scalable AI microservices, DevSecOps with advanced understanding of secrets management and security for AI including OWASP Top 10 for LLMs.

Roles & Responsibilities:

• Define and uphold engineering patterns for Python, React, and cloud services while leading the move from traditional logic to Agentic workflows.
• Drive the integration of AI throughout the software lifecycle and implement Model Context Protocol to bridge local development environments with LLM-based assistants.
• Reinstate structured code reviews with focus on AI Governance and establish quality gates covering security, performance, LLM observability, hallucination mitigation, and bias detection.
• Mentor and upskill junior engineers on Agentic AI tools like GitHub Copilot, Cursor, and Agent Builder while shifting team focus from manual boilerplate to high-level system design.
• Optimize cloud architectures for cost-efficiency and lead AI FinOps by balancing token usage, model selection, and inference costs against business outcomes.
• Partner with business partners to scope work using RAG and semantic search patterns to unlock value from enterprise data.

Experience Required: 10+ years in software engineering with 5+ years in a Technical Lead role. Hands-on LLM integration, prompt engineering, and orchestration frameworks experience required. Expert-level Azure or AWS experience with proficiency in Infrastructure as Code and building AI-ready CI/CD pipelines. Expertise in REST, event-driven architectures, and emerging protocols

Key Skills

Education

Any Graduate