Full stack Java + AI/ML

We are Hiring: Lead AI/ML Full-Stack Engineer
📍 Location: Remote / Hybrid
💼 Employment Type: Full-Time / Contract
🏢 Company: TechnoDeed Services
Are you an engineering leader who doesn’t just use AI tools, but actively architects and builds with them?
At TechnoDeed, we are expanding our high-impact, AI-first delivery PODs. We are seeking a visionary Lead AI/ML Full-Stack Engineer to design and operationalize multi-agent systems that drive and accelerate the modern AI-Driven Software Development Lifecycle (AIDLC).
Key Responsibilities
Agentic AI Architecture: Design, build, and deploy production-grade Agentic AI workflows and intelligent autonomous agents embedded across the delivery lifecycle.
Full-Stack Engineering: Lead the architecture of enterprise-scale, distributed applications utilizing modern Java backends and resilient React frontends.
Cloud & Platform Modernization: Deploy secure, containerized microservices across Microsoft Azure, AKS, and OpenShift environments.
AI-First Delivery & Mentorship: Drive high-velocity engineering by championing deep generative AI adoption (GitHub Copilot, M365 Copilot, LLM tooling) and mentoring pod engineers on best practices.
System Observability & Reliability: Establish deep telemetry, logging, and performance monitoring across hybrid cloud deployments to maintain high availability and low latency.
Required Qualifications
Experience: 12+ years of progressive software engineering and technical leadership experience.
Agentic AI & AIDLC: Hands-on experience developing autonomous AI agents, prompt architectures, agentic orchestrations, and integrating AI into the SDLC.
Backend Mastery: Deep proficiency in Java/J2EE, Spring Framework (Core, Boot, Batch), RESTful APIs, and microservices architecture.
Modern Frontend: Strong hands-on background in React (16+), Next.js, modern JavaScript, HTML5/CSS3, and modular UI components.
Data Engineering & APIs: Solid experience with relational databases (PostgreSQL, SQL) and GraphQL schema/API design.
Cloud & Containerization: Production expertise with Microsoft Azure, Azure Kubernetes Service (AKS), Red Hat OpenShift, Docker, Artifactory, and GitHub Actions.
Observability & Analytics: Hands-on experience tracking system health and debugging via Splunk, Azure KQL, Grafana, and Dynatrace.
AI-Assisted Engineering: Demonstrated weekly high-frequency usage (90%+) of GitHub Copilot, M365 Copilot, and generative AI developer tooling.
Methodology: Proven leadership in Agile/Scrum delivery environments.
Preferred Qualifications
Healthcare Domain Depth: Prior domain experience in Healthcare & Life Sciences, specifically with Utilization Management (UM), Prior Authorization (PA), Care Management, or Optum Clinical Manager (OCM) platforms.
How to Apply
If you are ready to build the future of autonomous enterprise engineering, we would love to connect.
📩 Send your updated resume to: talent@technodeedservices.com

Work arrangement
Yes