We are looking for a highly skilled Senior Agentic AI Engineer with strong expertise in Agentic AI, Large Language Models, RAG, AI Agents, and Python.

This role is ideal for someone who can go beyond writing prompts or individual agent code and take ownership of architecting end-to-end AI solutions. You will design and build AI-powered applications involving intelligent agents, search and retrieval pipelines, LLM orchestration, data ingestion, vector databases, and backend APIs.

The ideal candidate will have solid problem-solving capabilities and the ability to make architectural decisions around AI workflows, data models, retrieval strategies, model integrations, and overall solution design.

Title : Senior Agentic AI Engineer

Location :Remote Work

Employment Type: Full-time

Exp Range : 3 - 5 years

Key Responsibilities

- Architect and develop end-to-end Generative AI and Agentic AI solutions based on business and technical requirements.
- Design and build scalable AI Agent workflows, including agent orchestration, tool/API integrations, and multi-step AI workflows.
- Design and implement robust RAG and enterprise search pipelines for document and knowledge-based applications.
- Build and optimize data ingestion pipelines, including document processing, chunking, embeddings, indexing, retrieval, re-ranking, and context management.
- Design appropriate data models and storage strategies for vector databases to support efficient search and retrieval.
- Work with multiple LLMs and AI services and integrate them into production applications.
- Evaluate and optimize LLM applications for response quality, retrieval accuracy, relevance, latency, and overall performance.
- Develop scalable and production-quality Python applications and APIs using FastAPI.
- Write Python code supporting AI agents, LLM integrations, retrieval pipelines, and backend services.
- Apply strong knowledge of OOP, asynchronous programming, APIs, and problem-solving while developing AI applications.
- Work with SQL and NoSQL databases, caching technologies, and messaging/event-driven systems where required.
- Integrate AI applications with external APIs, data sources,



models, and enterprise systems.
- Collaborate with engineering and product teams to translate business requirements into scalable AI architectures.
- Contribute to technical decisions, solution architecture, and best practices for production AI applications.

Required Skills:

- Agentic AI & Generative AI: Strong hands-on experience building LLM-powered and Agentic AI applications, including AI Agents, agent orchestration, tool/API integration, prompt engineering, and multi-step AI workflows.
- RAG & Search Architecture: Strong experience designing and implementing RAG, enterprise search, and retrieval pipelines, including document ingestion, chunking, embeddings, indexing, retrieval, re-ranking, and context management.
- Vector Databases & Data Modeling: Hands-on experience working with vector databases, embeddings, and data modeling, with the ability to design how data is structured, stored, indexed, and retrieved for AI/search applications.
- AI Solution Architecture: Ability to design and architect end-to-end AI solutions—from data ingestion and search architecture to LLM integration, AI Agent workflows, and production implementation.
- LLM Evaluation & Optimization: Experience evaluating and optimizing LLM and RAG applications for accuracy, relevance, retrieval quality, latency, reliability, and overall response quality.
- Python & APIs: Strong Python programming skills with hands-on experience in OOP, asynchronous programming, problem-solving, and building APIs using FastAPI. Ability to write production-quality Python code for AI Agents and AI applications.
- Databases & Backend Technologies: Experience working with SQL and NoSQL databases, caching technologies such as Redis, and messaging/event-driven systems such as Kafka,



Google Pub/Sub, RabbitMQ, or similar technologies.
- Cloud: Hands-on experience working with GCP or AWS and integrating cloud services into AI applications.
- Problem Solving: Strong understanding of Data Structures, Algorithms, and problem-solving, with the ability to apply these skills while designing and building scalable AI solutions.

Preferred Skills:

- Experience building and deploying production-grade AI or enterprise AI applications.
- Experience with Docker, containerization, and CI/CD pipelines.
- Experience working with multiple LLM providers and models.
- Exposure to LLM observability, monitoring, and evaluation frameworks.
- Understanding of AI application security and secure API development.

About Techolution:

Techolution is the world’s leading FEA – Full Enterprise Automation specialist. We are trusted by boards and executive leaders who need AI with real business outcomes. Despite Gen AI, LLMs, and billions in investment, most enterprise AI programs aren't delivering results.

Techolution fixes that with BPA 4.0. We take the power of big Tech’s Generic AI and multiply it with our Expert AI stack — resulting in business process automations that follow the same nuances as domain experts do on the job at an unprecedented speed.

Our platform has delivered over $900M in AI ROI for our clients in less than a year, all while increasing their AI Adoption by 10x.

Our 3 power moves for ROI from AI:

1. Value Finder - We Identify high-impact AI and automation opportunities in enterprises and build solutions that deliver measurable value in as little as 30 days.

2. 100K Challenge: Work on fast-paced AI initiatives where teams build solutions designed to generate 2× ROI within 100 days.

3. GE LEAP: Contribute to enterprise AI transformation through our partnership with Google, helping scale Gemini-driven solutions across organizations.

Visit us @www.techolution.com : To know more about our revolutionary core practices and getting to know in detail about how we enrich the human experience with technology.

📌 Senior AI Engineer (India)
🏢 Techolution
📍 India