We are seeking a talented Agentic AI Engineer to design, develop, and deploy advanced AI agents capable of autonomous reasoning, decision-making, and self-directed task execution. This role requires expertise in modern AI architecture, reinforcement learning, multi-agent solution frameworks, and the deployment of agentic AI solutions. You will collaborate with cross-functional teams to create intelligent systems that drive business value and innovation.

Key Responsibilities:

1. Design and Development:

- Build and optimize agentic AI systems (e.g., autonomous agents, multi-agent frameworks, LLM-powered agents, MCP, RAG, Agent Skills, Context Engineering, Agent Memory).

- Integrate agentic AI solutions with existing enterprise platforms and workflows.

- Work closely with product, data, and engineering teams to translate business requirements into AI solutions.

- Monitor agent behaviors, diagnose anomalies, and refine agent instructions as needed.

- Deploying agentic AI agents in production environments, ensuring reliability and performance.

- Developed feedback loops for continuous agent improvement.

- Conduct code reviews and mentor junior engineers.

- Contribute to AI architecture, technical standards, and roadmap planning.

Required Skills & Qualifications:

- 6+ years of hands-on experience in Artificial Intelligence, Machine Learning, or related field.

- Knowledge of developing Gen AI or AI/ML solutions from use case to production and an understanding of agentic or autonomous systems.

- Understanding of Infrastructure and DevOps related to Gen AI use case deployments including Cloud environments, Agent Hosting, CICD deployments, docker and Kubernetes.

- Proficiency in Python development and FastAPI/Flask framework along with SQL.

- Expertise with agentic AI frameworks and concepts - LangChain, LangGraph, ADK, AutoGen, Model Context Protocol (MCP), LLMs, Chain of Thought prompting, knowledge store, embeddings.

- Experience with RAG techniques for knowledge base retrievals from vector DB.

- Prompt engineering techniques and fine-tuning.

- Hands-on experience with model deployment (REST APIs, microservices, or cloud-based inference).

- Hands-on experience with building user experiences to support agent-based solutions.

- Experience with cloud platforms (AWS, Azure, or GCP) and AI services.

- Strong problem-solving and analytical skills.

- Excellent communication and cross-functional collaboration abilities.

Preferred / Nice-to-Have Skills:

- Understanding of: Machine Learning algorithms, Deep Learning (CNNs, RNNs, Transformers), Natural Language Processing (NLP) and/or Computer Vision.

- Experience with data processing and analysis using NumPy, Pandas, and SQL.

- Familiarity with MLOps practices (model versioning, monitoring, CI/CD).

- Experience with Generative AI and LLMs (OpenAI, Hugging Face, LangChain, RAG pipelines).

- Experience with big data tools (Spark, Kafka).

- Familiarity with ethical AI, bias mitigation, and model governance.

- Prior experience leading AI initiatives or mentoring teams.

What We Offer:

- Competitive compensation and benefits.

- Flexible work arrangements.

- Opportunity to work on cutting-edge AI and GenAI projects.

- Continuous learning and professional development.

- Collaborative and innovation-driven culture.