Artificial Intelligence Engineer

Job Title: AI Engineer

Experience: 35 Years

Department: Engineering

Employment Type: Full-Time

About the Role

We are looking for a highly skilled Agentic AI Engineer to design, build, and deploy intelligent AI

agents capable of autonomous decision-making and task execution. The ideal candidate will have

hands-on experience working with multiple Large Language Models (LLMs), agent frameworks,

vector databases, and cloud platforms, along with strong DevOps and production deployment

awareness.

You will be responsible for building AI-driven systems using agentic architectures, integrating

LLMs with tools, APIs, and data sources to create scalable and reliable enterprise AI applications.

Key Responsibilities

Design and implement agentic AI architectures for autonomous task execution and

decision-making.

Develop and deploy LLM-powered applications and AI agents for real-world business use

cases.

Integrate multiple LLM providers (OpenAI, Anthropic, open-source models, etc.) into AI

systems.

Build and manage Retrieval-Augmented Generation (RAG) pipelines using vector

databases.

Develop solutions using AI frameworks such as Lang Chain, LlamaIndex, Autogen, Crew

AI, or similar.

Work with multiple vector databases for semantic search and memory management.

Design multi-agent systems that collaborate to solve complex tasks.

Deploy AI solutions across multi-cloud environments (AWS, Azure, GCP).

Implement CI/CD pipelines, containerization, and infrastructure automation for AI

workloads.

Monitor and optimize AI model performance, cost, latency, and reliability.

Collaborate with data engineers, ML engineers, and product teams to deliver AI solutions.

Ensure security, governance, and responsible AI practices.

Required Skills

Strong experience with Python and AI/ML development.

Hands-on experience with multiple LLMs (OpenAI, Anthropic, Cohere, Mistral, Llama, etc.).

Experience building agent-based AI systems.

Experience with AI orchestration frameworks (LangChain, LlamaIndex, CrewAI, AutoGen,

or similar).

Hands-on experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma,

or FAISS.

Experience implementing RAG architecture.

Knowledge of prompt engineering and LLM optimization techniques.

Experience deploying solutions on AWS / Azure / GCP.

Familiarity with Docker, Kubernetes, CI/CD pipelines, and DevOps practices.

Strong understanding of API integration and microservices architectures.

Good to Have

Experience with fine-tuning or parameter-efficient tuning of LLMs.

Knowledge of LLM Ops / ML Ops tools.

Experience with evaluation frameworks for LLMs.

Familiarity with knowledge graphs and semantic search.

Experience building AI copilots, chatbots, or autonomous agents.

Understanding of data privacy, model governance, and responsible AI practices.

Education

Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science,

or related field.

Preferred Candidate Profile

Strong problem-solving mindset with the ability to design scalable AI systems.

Experience working in fast-paced AI product environments.

Ability to stay updated with rapidly evolving LLM and AI agent ecosystems.

Excellent collaboration and communication skills.