AI Engineer

JOB DESCRIPTION

Location

Bangalore / Jaipur

Our Mission at In Time Tec

At In Time Tec, we believe in creating abundance through trust, transparency, and long-term partnerships. As a global technology company, we empower businesses to transform digitally with scalable software solutions, strategic consulting, and a people-first approach. With a presence across Europe, US, Australia, Arabia and Asia, In Time Tec has delivered over 1000 successful projects across industries.

We Are looking for

AI/ML Specialist

We are committed to building a future in which advanced technologies drive scalable impact and create measurable value for businesses, communities, and individuals. As part of our continued expansion in AI capabilities, we are seeking an AI/ML Engineer with a strong Data Science foundation and 1.5+ years of hands-on experience in designing, developing, and deploying Generative AI systems.

The ideal candidate will be responsible for implementing end-to-end intelligent solutions, including model development, fine-tuning, evaluation, and integration into enterprise environments. This includes working with LLMs, agentic workflows, and ML pipelines to deliver reliable, production-grade systems that address complex operational and business challenges.

This position is well suited for individuals who are driven to build robust, production-ready AI solutions, not just proof-of-concepts and who aspire to contribute to the evolution of next-generation agentic, autonomous, and ML-powered platforms.

Key Responsibilities

Machine Learning & Data Science

• Develop, train, and deploy machine learning models to solve high-impact business problems.
• Perform data preprocessing, feature engineering, and exploratory data analysis to ensure high-quality model input.
• Monitor, evaluate, and optimize model performance using industry best practices.
• Ensure ethical and compliant use of AI technologies across projects.

GenAI & Agentic AI Development

• Build and deploy AI agents using frameworks such as LangChain, CrewAI, LangGraph, Google ADK, or similar.
• Develop intelligent multi-agent workflows that can reason, act, and deliver automated outcomes.
• Integrate and experiment with LLMs from OpenAI, Mistral, Llama, Gemini, Claude, etc.
• Implement RAG pipelines, vector stores (FAISS, Qdrant, Weaviate), knowledge graphs, and other context-injection techniques.
• Continuously test and refine agent behaviour across real enterprise domains (utilities, legal, marketing, supply chain, etc.).

Engineering & Collaboration

• Design, build, and maintain scalable AI agentic systems, infrastructure, and APIs.
• Collaborate with data engineers, architects, product managers, and domain experts to integrate AI into production systems.
• Troubleshoot, debug, and improve AI workflows, pipelines, and model behaviour.
• Document designs, models, workflows, and architectural decisions to ensure reproducibility and team-wide knowledge sharing.
• Participate in code reviews and contribute to evolving our internal AI platform.

Required Qualifications

• Experience of building and deploying machine learning systems in production.
• Experience of building and deploying AI agents using open-source agentic frameworks.
• 1.5+ years hands-on experience delivering enterprise-level GenAI solutions (LLMs, agents, RAG, vector stores).
• Strong programming skills in Python (Async, Fast API; Java is a plus).
• Proficiency with ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
• Experience working with LLMs (OpenAI, Llama, Claude, Gemini, Mistral, etc.).
• Experience with cloud platforms: AWS, Azure, or GCP.
• Strong analytical, problem-solving, and communication skills.
• Ability to work collaboratively across technical and non-technical teams.
• Experience with multi-agent architectures or fine-tuning/customizing LLMs.
• Knowledge of graph databases (Neo4j) and advanced knowledge systems.
• Hands-on experience with LangGraph or Google ADK.
• Curiosity driven approach and capacity to acquire new skills rapidly.
• Experience in breaking down complex technical problems and developing high-quality MVPs efficiently

Nice to Have

• Certifications in Data, ML, Cloud, or AI domains.

Educational Background

• Bachelor's or master’s degree in computer science, Data Science, Engineering, or related field.