Senior AI/ML Engineer

2366682 - Senior AI/ML Engineer

Grade SG2 8

Location Bangalore (2 open positions), Hyderabad (2 open position)

Shift General Shift

Budget 61 LPA - 62 LPAFixed Max Please note that any offer extended by us will depend on multiple factors, including the candidates current compensation and overall profile evaluation. Therefore, I would recommend having an open-ended discussion with the candidates regarding compensation and setting realistic expectations early in the process.

Job Summary

We are seeking a highly skilled AI/ML Engineer to design, develop, and deploy scalable Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) solutions that address complex business challenges. The ideal candidate will have extensive experience building production-grade AI systems, developing LLM-powered applications, and integrating AI capabilities into enterprise platforms. This role requires expertise across the AI/ML lifecycle, cloud technologies, MLOps/LLMOps practices, and modern Generative AI frameworks.

Key Responsibilities

AI Machine Learning Development

• Design, develop, and implement AI, Machine Learning, and Generative AI solutions for business use cases.
• Analyze business problems and recommend appropriate AI approaches, including ML models, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, prompt engineering, and cloud AI services.
• Develop, evaluate, deploy, and continuously improve machine learning models and AI-driven solutions.
• Build scalable AI/ML pipelines for data processing, model training, validation, deployment, monitoring, and retraining.

Generative AI LLM Solutions

• Build and integrate LLM-based applications using prompt engineering, orchestration frameworks, semantic search, vector databases, and model evaluation techniques.
• Develop and implement RAG architectures leveraging embeddings and vector search technologies.
• Evaluate and optimize GenAI applications for quality, accuracy, latency, security, scalability, and cost efficiency.
• Monitor and address hallucinations, model drift, and performance degradation in production environments.

Cloud Platform Integration

• Integrate AI/ML and GenAI solutions into enterprise applications, APIs, workflows, and business platforms.
• Utilize cloud-based AI platforms and data ecosystems such as Microsoft Azure, AWS, Google Cloud Platform (GCP), Databricks, Kubernetes, and serverless services.
• Design and deploy scalable, secure, and reliable AI solutions within modern cloud architectures.

MLOps LLMOps

• Apply MLOps and LLMOps best practices, including CI/CD pipelines, model versioning, experiment tracking, deployment automation, and performance monitoring.
• Establish automated testing, retraining, and governance processes for AI solutions.
• Ensure model reliability, scalability, and operational excellence across AI deployments.

Responsible AI Governance

• Implement responsible AI practices, including data privacy, explainability, bias mitigation, access controls, prompt safety, and regulatory compliance.
• Ensure alignment with organizational governance, security, and risk management requirements.

Collaboration Leadership

• Communicate complex AI/ML concepts and analytical findings to technical and non-technical stakeholders.
• Partner with engineering, product, business, and data teams to deliver impactful AI-driven solutions.
• Serve as a technical resource and mentor to junior team members.

Required Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field.
• 7+ years of experience in Software Engineering, Data Science, Machine Learning, AI Engineering, or related technical disciplines.
• 5+ years of hands-on experience developing, deploying, and maintaining machine learning models and AI solutions in production environments.
• Strong experience in Generative AI solution design and implementation.

Required Technical Skills

• Hands-on experience with:
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • Embeddings and Semantic Search
  • Vector Databases
  • Model Evaluation and Optimization
• Strong programming skills in Python and SQL.
• Experience developing REST APIs and integrating AI services into enterprise applications.
• Proficiency with AI/ML frameworks and libraries such as TensorFlow, Py…