AI / ML Developer (Lead)

TENARAI TECHNOLOGIES PRIVATE LIMITED; Dadri, Pune District, Bengaluru; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

TENARAI TECHNOLOGIES PRIVATE LIMITED is seeking a Lead AI/ML Engineer with extensive hands-on experience to design and deliver advanced AI solutions as Data Scientist. You will lead model development, evaluation, and deployment across GenAI, NLP, anomaly detection, and prediction tasks.

You will design data pipelines, build scalable AI systems, optimize vector databases, and collaborate with data engineering teams while mentoring a team of AI/ML engineers in an on-site role in Uttar Pradesh.

Qualifications

• Lead the design, development, and deployment of ML models and Generative AI solutions.
• LLMs (OpenAI, Llama, Mistral, etc.) experience.
• LangChain / LlamaIndex experience.
• RAG architectures experience.
• AI Agents / multi-agent systems experience.
• Build and optimize ML models (NLP, predictive, recommendation, anomaly detection).
• Develop and implement AI agents and automation use cases such as copilots, RCA, and intelligent ticketing systems.
• Guide and mentor a team of AI/ML engineers and data scientists, ensuring best practices in coding, architecture, and delivery.
• Collaborate with data engineering and business teams to translate requirements into end-to-end AI solutions.
• Implement MLOps/LLMOps pipelines, including CI/CD, model monitoring, and lifecycle management.
• Strong proficiency in Python.
• Microservices architecture.
• Git, CI/CD pipelines.

Responsibilities

• Lead the design, development, and deployment of ML models and Generative AI solutions.
• Develop and deploy scalable GenAI systems and data pipelines.
• Design and evaluate prompts, embeddings, and response quality for GenAI applications.
• Build AI agents, multi-agent systems, and decision flows.
• Develop APIs/microservices (FastAPI, backend services).
• Handle vector DB setup and performance tuning.
• Integrate with enterprise tools and data flows.
• Mentor a team of AI/ML engineers and data scientists; collaborate with cross-functional teams.

Job description

Job Description:

• We are looking for a Lead AI/ML Engineer with 10+ years of experience, including 57 years of hands-on experience in Machine Learning and Generative AI, to lead the design and delivery of advanced AI solutions as Data Sceintist.
• Key responsibilities & Hands-on experience with:
• Can do Model Development (Core Responsibility)
• Can build & refine ML models for use cases like anomaly detection, forecasting, classification, and RCA (root cause analysis).
• Can perform data exploration, feature engineering, and statistical analysis to improve model accuracy and insights
• Can design and evaluate LLM prompts, embeddings, and response quality for GenAI applications (RAG, copilots)
• Can work on to build Agents, Multi-agents, Decision Flows
• Can build scalable AI systems as GenAI / Engineer
• Will Design and Implement data pipelines (ingestion ? preprocessing ? embeddings ? storage)
• Will Generate design prompts for: Root cause explanation, Failure reasoning, Contextual insights
• Will Develop APIs/microservices (FastAPI, backend services)
• Will Handle vector DB setup & performance tuning
• Will Integrate with Enterprise tools like QIR systems, model outputs, APIs,UI / dashboards
• Will Manage data flow between systems

Required Skills & Qualifications

• Lead the design, development, and deployment of ML models and Generative AI solutions
• LLMs (OpenAI, Llama, Mistral, etc.)
• LangChain / LlamaIndex
• RAG architectures
• AI Agents / multi-agent systems"
• Build and optimize machine learning models (NLP, predictive, recommendation, anomaly detection) and ensure production-grade performance and scalability
• Develop and implement AI agents and automation use cases such as copilots, RCA, and intelligent ticketing systems
• Guide and mentor a team of AI/ML engineers and data scientists, ensuring best practices in coding, architecture, and delivery
• Collaborate with data engineering and business teams to translate requirements into end-to-end AI solutions
• Implement MLOps/LLMOps pipelines, including CI/CD, model monitoring, and lifecycle management
• Strong proficiency in Python
• Microservices architecture
• Git, CI/CD pipelines