Senior AI Engineer

Agentic Engineering & Orchestration 

• Workflow Design: Architect complex, multi-agent workflows using Microsoft AI tech stack. Design, Develop and Deploy agents to handle loops, interruptions, and human-in-the-loop interventions.
• Tool Use & Function Calling: Build reliable “tool layers” that allow LLMs to safely interact with internal APIs, databases, and third-party SaaS platforms (e.g., SalesForce, Workday, ServiceNow etc.)
• State Management: Design persistence layers to manage agent memory, conversational history, and context windows efficiently.

Advanced Data & RAG Strategy

• Retrieval Pipelines: Build production-grade data retrieval and integration systems. Optimize vector indexing, document chunking, and re-ranking algorithms to ensure high-precision context retrieval.
• Data Quality: Collaborate with Data Engineers to curate “Golden Datasets” for agent consumption

LLMOps, Evaluation & Quality

• Automated Evaluation: Build CI/CD pipelines for AI that include “LLM-as-a-Judge” testing. Leverage frameworks to score agent outputs for accuracy, hallucination, and safety before deployment.
• Observability: Instrument applications with tracing tools to visualize agent reasoning chains, monitor latency, and debug failures in production.
• Cost Optimization: Monitor token usage and latency, optimizing prompt density and caching strategies to maintain high performance at sustainable costs.

Innovation & Collaboration

• Prototyping to Production: Rapidly validate new ideas using state-of-the-art models, then refactor successful prototypes into maintainable, tested production code.
• Standards Adoption: Stay ahead of the curve by evaluating emerging technologies to standardize agent connectivity.

• Bachelor’s degree and 5 years of software engineering experience, with exposure to AI/ML applications OR 9 years of software engineering experience, with exposure to AI/ML applications.
• Programming: Strong hands-on experience with Python for AI/LLM application development.
• Agentic AI: Hands-on experience designing and building AI agents / Agentic AI solutions.
• LLM APIs: Experience integrating and working with LLM model APIs (e.g., OpenAI, Azure OpenAI, Anthropic, Gemini).
• AI Specialization: 2+ years specifically building with LLMs, with deep familiarity in:
  Orchestration: LangChain, LangGraph, or similar state-based frameworks.
  Vector DBs: Pinecone, Weaviate, or pgvector.
  Prompt Engineering: Advanced techniques (Chain-of-Thought, ReAct, Few-Shot).
• Strong experience with React, TypeScript, Vite, Python, FastAPI, and REST API development
• Hands-on experience with Azure cloud services, including Azure Storage, Key Vault, Monitor, Application Insights, and Azure AI Search
• Knowledge of secure enterprise application development, including OAuth 2.0, JWT, Microsoft Entra ID, RBAC, and secrets management
• Experience with DevOps and CI/CD, including GitHub or Azure DevOps, Docker, YAML pipelines, and deployment troubleshooting
• Experience with document ingestion, structured/unstructured data processing, observability, logging, testing, and production support
• Production Mindset: Experience not just building demos, but operating them. You know how to handle rate limits, context window overflows, and non-deterministic errors.
• Soft Skills: Ability to explain “probabilistic software” to non-technical stakeholders—managing expectations that agents are never 100% accurate, but can be 100% useful.
• Communication: Excellent communication skills, with experience in documenting technical designs, sharing insights, and enabling team knowledge transfer.