Agentic AI Engineer

Job Title:

Location:

Experience:

Skill Areas:

Industry:

Role Overview:

AI agentbased systems

Python or Java

Key Responsibilities:

• Design and implement

  Agentic AI architectures

  including multi-agent systems, planning, reasoning, and task orchestration.
• Build end-to-end

  AI agents

  using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or similar.
• Develop and integrate

  AI/ML components

  , including model training, fine-tuning, and inference.
• Work with

  LLMs (GPT, Llama, Mistral, Claude, Gemini, etc.)

  for building conversational, decision-making, and autonomous workflows.
• Implement

  RAG pipelines

  using vector databases (FAISS, Pinecone, Chroma, Weaviate).
• Integrate agents with

  APIs, tools, plugins, enterprise systems

  , and automation workflows.
• Optimize model performance, latency, cost, and hallucination reduction.
  
• Collaborate with product, engineering, and data teams to understand problem statements and define agent behaviors.
  
• Develop reusable components, prompt templates, reasoning chains, evaluators, and monitoring frameworks.
  
• Work on

  LLM safety, guardrails, evaluation

  , and bias reduction.
• Deploy AI agents in

  cloud environments

  (AWS, GCP, Azure) using containerized infrastructure.
• Ensure code quality, testing, CI/CD, and maintainability.
  

Must-Have Skills:

AI/ML & LLM Skills:

• Strong understanding of

  machine learning

  , NLP, generative AI, and foundational model concepts.
• Hands-on experience with

  LLM fine-tuning, prompt engineering, RAG

  , and vector-based retrieval.
• Experience with

  agent frameworks

  like:
• LangChain / LangGraph
  
• LlamaIndex
  
• AutoGen / CrewAI
  
• Haystack (optional)
  

Programming Skills:

• Strong coding experience in

  Python

  or

  Java

  (Python preferred for AI workflows).
• Experience with ML/DL libraries:

  PyTorch, TensorFlow, Hugging Face Transformers

  .

System & Cloud Skills:

• Experience with

  cloud deployments

  (AWS / Azure / GCP).
• Exposure to

  MLOps

  , CI/CD, containerization (Docker, Kubernetes).
• Experience working with REST APIs, microservices, and event-driven systems.
  

Nice-to-Have Skills:

• Experience with

  Autonomous Agents

  , planning algorithms, reinforcement learning, or multi-agent systems.
• Knowledge of

  AI safety, guardrails, red teaming

  , evaluation frameworks.
• Experience building

  AI copilots

  , AI automation bots, or enterprise AI assistants.
• Familiarity with

  OpenAI, Anthropic, Google Vertex AI, AWS Bedrock, Azure OpenAI

  .
• Experience with

  Graph databases

  , knowledge graphs, and semantic search.

Qualifications:

• Bachelors or Master’s degree in Computer Science, AI/ML, Data Science, Engineering, or related field.
  
• 5–10 years of hands-on experience in

  AI/ML, NLP, or backend engineering

  .
• 1–3 years of experience working with

  LLMs, GenAI, or AI agents

  (preferred but not mandatory if they have strong ML + Python experience).

Preferred Background:

• Experience in

  product development

  , enterprise AI platforms, AI SaaS, fintech, IT services, or automation platforms.
• Prior experience delivering

  end-to-end AI solutions

  from design to deployment.