Hiring for AIML.
Job Description for an AI Engineer
Job Title: Lead AI Engineer
Location
Bengaluru – Hybrid mode
Experience
10+ years in Software Engineering development with 4-6 years in AI/ML and Generative AI.
Job Summary
We are looking for a highly skilled and innovative AI Engineer to design, develop, deploy, and optimize AI-powered solutions that address complex business challenges. The ideal candidate should have a strong foundation in Java-based application development and hands-on experience in Machine Learning, Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Multi-Agent Systems, MLOps, and cloud-based AI services.
This role involves designing and building end-to-end, production-ready AI applications, integrating AI capabilities into enterprise platforms, and developing scalable, secure, and high-performing solutions. The candidate will work closely with cross-functional teams, including product managers, architects and software engineers, to deliver innovative AI-driven solutions that create measurable business value. Additionally, the role requires providing technical leadership, mentoring engineering teams, and driving the adoption of AI best practices across the organization.
Key Responsibilities
- Design, develop, and deploy enterprise AI and Generative AI solutions.
- Build production-ready applications using LLMs, RAG, and AI Agent frameworks.
- Develop intelligent AI agents and multi-agent workflows to automate business processes.
- Integrate AI services with enterprise applications, databases, APIs, and third-party platforms.
- Design, deploy, and manage AI solutions on cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP).
- Optimize prompts, model performance, accuracy, and reliability for business use cases.
- Collaborate with cross-functional teams to identify and deliver AI-driven solutions.
- Ensure scalability, security, observability, and reliability of AI applications.
- Participate in architecture reviews, code reviews, and technical design discussions.
- Monitor, troubleshoot, and optimize application performance, latency, and cost.
- Translate business requirements into effective AI-powered solutions.
- Mentor engineering teams on AI/ML, Generative AI, and software engineering best practices.
- Drive technical innovation and establish reusable AI frameworks, standards, and best practices.
Required Skills
Programming & Software Engineering
- Min of 8 years of hands-on programming experience in Java.
- Hands-on experience with any of the ORM technologies such as Hibernate, JPA, or Spring Data JPA.
- Experience working with modern front-end frameworks, preferably ReactJS.
- Strong proficiency in Python for AI/ML development, data processing, and automation.
- Experience on SQL and NO SQL databases.
- Solid understanding of software engineering principles, object-oriented programming, and application design.
- Experience building scalable, secure, and high-performance enterprise applications.
- Familiarity with version control systems such as Git and collaborative development practices.
Generative AI & Large Language Models (LLMs)
- Hands-on experience developing applications using OpenAI, Azure OpenAI, Anthropic Claude, Llama, or similar Large Language Models (LLMs).
- Strong understanding of:
- Prompt Engineering
- Context Management and Conversation Memory
- LLM Evaluation and Performance Assessment
- AI Safety Guardrails and Risk Mitigation
- Responsible AI Principles and Best Practices
- Experience integrating LLMs into enterprise applications and business workflows.
- Ability to optimize model responses for accuracy, reliability, performance, and cost efficiency.
RAG & Knowledge Retrieval
- Experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
- Strong understanding of vector databases, embedding models, semantic search, and knowledge retrieval techniques.
- Experience building enterprise search and question-answering solutions using RAG architecture.
- Familiarity with Pinecone, Weaviate, Chroma, FAISS, Azure AI Search, or similar vector database technologies.
- Experience developing data ingestion, indexing, and retrieval pipelines for structured and unstructured data.
AI Agents & Orchestration
- Experience designing and developing AI agents and multi-agent workflows for business process automation.
- Hands-on experience with agent orchestration frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
DevOps & MLOps
- Experience with Git, Docker, and Kubernetes.
- Knowledge of CI/CD pipelines and automation using Azure DevOps or GitHub Actions.
- Familiarity with MLflow for experiment tracking and model lifecycle management (preferred).
- Understanding of MLOps practices, including model deployment, versioning, monitoring, and maintenance.
- Ability to build and support scalable, reliable, and secure deployment pipelines for AI applications
