Senior Agentic AI Engineer

Agentic AI Development
Architect and implement multi‑agent orchestration frameworks (Orchestrator/Supervisor agents, A2A agents with enterprise service integrations).
Build reusable agent registries for custom agents across multiple tenants and cloud environments.
Define Human‑in‑the‑Loop and Human‑on‑the‑Loop patterns for enterprise workflows.
• Cloud & Production Deployment
Lead AWS AgentCore development and migration (Dev/QA/Prod environments).
Deploy LLMaaS and QAaaS services on AWS with focus on scalability, automation, and bug‑free production rollout.
Integrate agents into enterprise portals and applications (e.g., dashboards, workflow orchestration tools, analytics platforms).
• Governance & Compliance
Enhance AI guardrails, documentation, and compliance frameworks for regulated industries.
Define AI testing strategies and standards for enterprise validation.
• Monitoring & Reliability
Strengthen monitoring foundations across API gateways, event streaming platforms, container orchestration, observability tools, and backend services.
Establish baseline health metrics (latency, throughput, error rates, uptime).
Implement failure visibility and alerting protocols across integration layers.
• Innovation & Scaling
Drive modernization of QAaaS platform across AWS, distributed databases, and parser integrations.
Explore advanced GenAI techniques (adaptive prompting, retrieval‑augmented generation, multi‑modal agents).
Collaborate with cross‑functional teams to onboard new services into the enterprise AI foundation.

Essential functions

5+ years in AI/ML engineering, with 3+ years in GenAI/LLM projects.
Strong expertise in AWS cloud services (SageMaker, Bedrock, ECS/EKS, Lambda).
Hands‑on experience with LLM frameworks (LangChain, Lyzr, RAG pipelines).
Proven track record of production‑level deployments in enterprise environments.
Familiarity with multi‑agent orchestration and agent factory concepts.
Strong knowledge of Python, APIs, microservices, CI/CD pipelines.
Experience in enterprise governance, compliance, and monitoring frameworks.
Excellent communication skills to distill technical achievements into executive‑ready messaging.

Preferred Qualifications
Background in regulated industries or enterprise AI delivery.
Experience with QA automation and LLM‑based validation metrics.
Knowledge of data privacy, security, and enterprise risk mitigation.

Ability to lead cross‑functional teams with empathy and precision.

Qualifications

Programming: Advanced Python (OOP, async), REST API frameworks (Flask, FastAPI)

Cloud: Strong experience with Microsoft Azure (App Services, Azure Functions, Blob Storage, Cosmos DB preferred)

GenAI/LLM Ecosystem: Familiarity with LangChain, LangGraph, or similar orchestration frameworks Experience building solutions with RAG design patterns and prompt tuning (CoT, ToT, FewShot) Understanding of vector databases (e.g., FAISS, Pinecone, Azure Cognitive Search) Embedding models like Sentence Transformers, CLIP/SIGLIP, or similar

Performance Optimization: Hands-on experience scaling solutions for high payload volumes Token management and handling long-form data inputs

Data Integration: Ability to work with semi-structured and structured data formats, schema mapping, and transformation

Version Control & CI/CD: Git, Azure DevOps/GitHub Actions pipelines