Ai Ml Engineer

Timecode Technologies; Hyderabad; On-site; INR 4,000,000 - 5,600,000; Full time

Job summary

Timecode Technologies is seeking an experienced AI/ML Engineer in Hyderabad to design and implement autonomous AI systems. You will work on advanced agentic AI architectures, LLM-driven tooling, and secure, scalable deployments in cloud environments.

The role requires deep expertise in Python, distributed systems, MLOps, and tool orchestration with a focus on production-ready AI solutions for enterprise applications. Primarily on-site, five-day workweeks in Hyd.

Qualifications

• 6+ years of software/AI/ML engineering experience.
• Expert-level Python programming.
• Strong understanding of async programming, concurrency, task scheduling, and distributed systems.
• Hands-on experience building Agentic AI / autonomous AI systems.
• Strong understanding of LLMs, Generative AI, prompt engineering, and tool/function calling.
• Experience with LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or similar agent frameworks.
• Strong experience with RAG, embeddings, vector databases, chunking, retrieval, reranking, and context management.
• Experience implementing agent memory and state management.
• Experience with planning, reasoning, reflection, self-correction, validation, and re-planning.
• Experience deploying AI systems using Docker and Kubernetes.
• Strong experience with Azure, AWS, or GCP; Azure preferred.
• Experience with MLOps/AgentOps, CI/CD, observability, model/prompt versioning, and production deployment.
• Strong knowledge of AI security, prompt-injection mitigation, guardrails, access control, and secure tool execution.
• Experience integrating AI systems with REST APIs, databases, enterprise applications, and SaaS platforms.
• Working knowledge of SQL/NoSQL databases and event-driven architectures.

Skills

Years of experience

Python programming

Asynchronous programming

Distributed systems

Agentic AI / autonomous AI

LLMs / Generative AI

Prompt engineering

LangGraph

LangChain

AutoGen

CrewAI

Semantic Kernel

RAG / embeddings

Vector databases

Tool/function calling

Agent memory

Planning / reasoning

Docker

Kubernetes

Cloud (Azure/AWS/GCP)

MLOps / AgentOps

CI/CD

Security / guardrails

REST APIs / Databases

Tools

Azure Kubernetes Service

FAISS

Pinecone

Job description

Role & responsibilities

Exp: 6+yrs

Loc: Prim: Hyd, 5 days working

Required Skills

• 68+ years of software/AI/ML engineering experience.
• Expert-level Python programming.
• Strong understanding of async programming, concurrency, task scheduling, and distributed systems.
• Hands-on experience building Agentic AI / autonomous AI systems.
• Strong understanding of LLMs, Generative AI, prompt engineering, and tool/function calling.
• Practical experience with LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or similar agent frameworks.
• Strong experience with RAG, embeddings, vector databases, chunking, retrieval, reranking, and context management.
• Experience implementing agent memory and state management.
• Experience with planning, reasoning, reflection, self-correction, validation, and re-planning.
• Experience deploying AI systems using Docker and Kubernetes.
• Strong experience with Azure, AWS, or GCP; Azure is preferred.
• Experience with MLOps/AgentOps, CI/CD, observability, model/prompt versioning, and production deployment.
• Strong knowledge of AI security, prompt-injection mitigation, guardrails, access control, and secure tool execution.
• Experience integrating AI systems with REST APIs, databases, enterprise applications, and SaaS platforms.
• Working knowledge of SQL/NoSQL databases and event-driven architectures.

Keywords

Agentic AI, AI/ML Engineer, Generative AI, LLM, LLM Engineer, AI Agents, Autonomous Agents, Python, LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, RAG, Retrieval Augmented Generation, Azure OpenAI, Anthropic, OpenAI, AWS Bedrock, Vector Database, FAISS, Pinecone, Azure AI Search, Embeddings, Prompt Engineering, Tool Calling, Function Calling, Multi-Agent Systems, Agent Memory, MLOps, AgentOps, Docker, Kubernetes, Azure, AWS, GCP, LLM Evaluation, AI Security, Guardrails, Prompt Injection, CI/CD