Job Title: AI/ML Engineer – Agentic AI
Experience: 6–10 Years
Employment Type: Full-Time
Position Summary
We are seeking a highly skilled AI/ML Engineer – Agentic AI to design, develop, and deploy next-generation autonomous AI systems powered by Large Language Models (LLMs). The ideal candidate will have hands-on experience in building intelligent AI agents capable of reasoning, planning, tool execution, memory management, and enterprise workflow automation.
You will work closely with AI researchers, data scientists, software engineers, and business stakeholders to architect scalable Agentic AI solutions using modern AI frameworks, cloud platforms, and MLOps best practices.
Key Responsibilities
- Design, develop, and deploy autonomous AI agents capable of reasoning, planning, and executing complex multi-step tasks.
- Build Agentic AI systems using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, or similar.
- Develop intelligent workflows supporting goal decomposition, task orchestration, dynamic decision-making, and tool invocation.
- Integrate LLMs including OpenAI, Azure OpenAI, Anthropic, and open-source models into enterprise applications.
- Design robust prompt engineering strategies including Chain of Thought, Self-Reflection, ReAct prompting, and planning techniques.
- Implement Retrieval-Augmented Generation (RAG) solutions using vector databases such as FAISS, Pinecone, or Azure AI Search.
- Develop short-term and long-term memory architectures for conversational and autonomous AI systems.
- Build custom orchestration layers, tool execution pipelines, and secure function-calling mechanisms.
- Implement planning, feedback loops, guardrails, failure recovery, and action validation for reliable AI agents.
- Integrate AI agents with enterprise applications including CRM, ERP, databases, REST APIs, SaaS platforms, and internal services.
- Deploy AI applications using Docker, Kubernetes, and cloud-native architectures.
- Implement observability including prompt logging, tracing, monitoring, and performance analytics.
- Build CI/CD pipelines for AI models, prompts, and agent deployments.
- Design evaluation frameworks to measure task completion, latency, cost optimization, safety, and hallucination detection.
- Implement Responsible AI practices including explainability, bias mitigation, prompt injection prevention, and human-in-the-loop workflows.
- Collaborate with cross-functional teams to deliver scalable, secure, and production-ready Agentic AI solutions.
Required Technical SkillsProgramming & Software Engineering
- Expert-level Python programming
- Object-Oriented Programming (OOP)
- Async programming, concurrency, and multiprocessing
- API development using FastAPI or Flask
- Git and version control
Agentic AI
- Autonomous AI Agents
- Multi-step reasoning and planning
- Goal decomposition
- Task orchestration
- Dynamic decision making
- Stateful and stateless agents
- Memory management
- Tool calling and function execution
- ReAct architecture
- Plan-and-Execute
- Reflexive agents
- Hierarchical and multi-agent systems
Large Language Models (LLMs)
- OpenAI GPT
- Azure OpenAI
- Anthropic Claude
- Open-source LLMs (Llama, Mistral, etc.)
- Prompt Engineering
- Chain of Thought (CoT)
- Self-Reflection
- Few-shot & Zero-shot prompting
- Model selection and optimization
- LoRA/Fine-tuning (preferred)
Agent Frameworks
- LangGraph
- LangChain
- Semantic Kernel
- AutoGen
- CrewAI
- Custom orchestration frameworks
RAG & Knowledge Systems
- Retrieval-Augmented Generation (RAG)
- Vector Databases
- Pinecone
- FAISS
- Azure AI Search
- Embeddings
- Chunking strategies
- Context compression
- Knowledge Graphs (preferred)
Planning & Reasoning
- Task planning
- Re-planning
- Constraint-based execution
- Feedback loops
- Self-correction
- Tool reliability scoring
- Guardrails
- Failure detection
- Recovery mechanisms
MLOps & AgentOps
- Docker
- Kubernetes
- CI/CD pipelines
- Prompt versioning
- Model versioning
- Agent monitoring
- Tracing
- Logging
- Production deployment
- Serverless architectures
Evaluation & Testing
- Agent benchmarking
- Task success evaluation
- Latency optimization
- Cost optimization
- Reliability testing
- Hallucination detection
- A/B testing
- Simulation environments
Security & Responsible AI
- Prompt injection prevention
- Jailbreak mitigation
- Secure tool execution
- Identity & Access Management (IAM)
- Data privacy
- Responsible AI principles
- Explainable AI
- Human-in-the-loop systems
Data & Integration
- REST APIs
- GraphQL APIs (preferred)
- SQL
- NoSQL
- Enterprise integrations
- CRM/ERP systems
- Event-driven architecture
- Message queues (Kafka, RabbitMQ, Azure Service Bus preferred)
Cloud Platforms
- Microsoft Azure (Preferred)
- AWS
- Google Cloud Platform (GCP)
- Azure AI Services
- Azure OpenAI
- Azure AI Search
- Azure Functions
- Azure Kubernetes Service (AKS)
- Azure Key Vault
- Cloud identity and secrets management
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field.
- 6–10 years of software engineering experience with at least 3+ years in AI/ML and Generative AI.
- Hands-on experience delivering enterprise-grade Agentic AI or GenAI solutions.
- Experience building enterprise copilots, AI assistants, or autonomous workflow platforms.
- Strong understanding of distributed systems and cloud-native architectures.
- Excellent analytical, problem-solving, and communication skills.
Nice to Have
- Multi-agent collaboration systems
- Enterprise AI copilots
- Human-AI collaboration frameworks
- Reinforcement Learning (RL)
- RLHF
- Knowledge Graphs
- GraphRAG
- AI Governance
- AI Safety Engineering
- Azure Machine Learning
- MLflow
- Databricks
- NVIDIA AI ecosystem
What We Offer
- Opportunity to build cutting-edge Agentic AI solutions for enterprise-scale applications.
- Work with the latest LLMs, AI frameworks, and cloud technologies.
- Collaborative environment with AI researchers, architects, and engineering teams.
- Career growth in Generative AI, Agentic AI, and autonomous systems.
- Competitive compensation and comprehensive employee benefits.
Work Location: Hybrid remote in Noida, Uttar Pradesh (Noida)
