REMOTEFULLTIME
Lead AI & Machine Learning Engineer - Python | LLM | Temporal
Naveera Technology LLC
Remote · remote · Posted 2d ago
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Section · 01
About this role
Greetings of the day!!
I am Arumugam Veera, and I'm reaching out to you regarding an exciting opportunity with Naveera IT consulting. You can connect with me on LinkedIn https://www.linkedin.com/in/arumugamv
About Company Naveera is a trusted global engineering partner delivering Data Engineering, Generative AI, Application Development and IT Infrastructure solutions. With over 15 years of experience in IT services and consulting. we help organizations transform raw data into deployable business value. Our approach emphasises Production over Pilots we dont stop at proof-of-concepts; we engineer systems that go live, scale reliably, and deliver measurable outcomes. With our CoE-driven delivery model, product engineering DNA, and a scalable talent acquisition engine, we align deeply with enterprise demands for performance, compliance, continuity and innovation. From Digital Health to Financial Services, and E-Commerce to Technology, we serve a diverse industry base and back every engagement with proven frameworks, low-attrition teams and agile global delivery. At Naveera, we empower clients to turn challenge into growth, data into insight and concepts into platforms.
Website https://naveeratech.com/
Specialties Data Engineering & Modern Data Stack, Generative AI Solutions & Model Deployment, Application Development (Web, Mobile & Enterprise), Artificial Intelligence (Predictive, Conversational, Computer Vision)
Job Title: Lead AI & Machine Learning Engineer - Python | LLM | Temporal Experience: 8 Years
Job Location: Madurai, Tamil Nadu, India Shift: 2:00 PM 11:30 PM IST
Working Mode: Remote/Hybrid (Quarterly Once Travel would be required to the Madurai Location) Job Type: Full-Time
Role Overview We are looking for an experienced AI Lead to design and build enterprise- grade AI automation platforms. The ideal candidate will have strong expertise in Python development, workflow orchestration, API integrations, and AI agent frameworks. This role requires leading the technical implementation of scalable automation solutions while collaborating with cross-functional teams.
Key Responsibilities ● Lead the design and development of AI-driven automation workflows. ● Build scalable Python backend services (REST APIs, asynchronous processing, microservices). ● Design and implement workflow orchestration using Temporal (or similar workflow engines). ● Integrate Python services with C#/.NET, third-party platforms, and enterprise APIs. ● Develop AI Agent workflows using modern LLM frameworks and orchestration patterns with AWS Platform ● Implement secure authentication and authorization mechanisms (OAuth2, JWT, SSO, RBAC). ● Design event-driven and stateful/stateless backend architectures. ● Develop integrations with databases, message queues, and cloud services. ● Ensure code quality through testing, CI/CD, logging, monitoring, and documentation. ● Mentor developers and drive engineering best practices.
Required Skills Backend & APIs ● Strong expertise in Python ● FastAPI, Flask, or Django ● REST APIs, WebSockets, Async Programming ● Microservices architecture with containers ● External API integrations ● C#/.NET API integration experience Workflow & Automation ● Temporal (preferred) or equivalent workflow orchestration ● Event-driven architecture ● Background workers and distributed processing ● State management for long-running workflows AI & Automation ● AI Agent frameworks (CrewAI, AutoGen, Semantic Kernel, etc.) ● LLM integration ( Amazon Bedrock) ● Prompt engineering and Guardrails ● RAG architecture and vector databases ● MCP (Model Context Protocol) and SKILL knowledge is a plus Security ● OAuth2 ● JWT ● SSO integration ● RBAC/ABAC authorization ● API security and secrets management DevOps & Cloud ● Docker ● Git ● CI/CD pipelines ● AWS or Azure ● Monitoring and logging Databases ● Redshift / SQL Server ● Redis ● NoSQL databases ● Vector databases (ChromaDB, Pinecone, pgvector, etc.) Preferred Qualifications ● Experience building enterprise AI automation platforms. ● Knowledge of distributed systems and scalable backend architecture. ● Experience integrating AI solutions into existing enterprise applications. ● Strong debugging, problem-solving, and architecture skills. ● Previous experience leading technical teams and mentoring engineers. Nice to Have ● Kubernetes ● Kafka/RabbitMQ ● GraphQL ● Playwright or browser automation ● Enterprise integration patterns ● Infrastructure as Code (Terraform)
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Section · 02