AI Tech Lead

AI/Generative AI Tech Lead – LLM & RAG

Position Overview Build and deploy AI and Generative AI solutions that address real-world business problems, from proof-of-concept through production. This role combines hands-on AI/ML engineering with technical leadership, working with senior engineers, architects, data scientists, and business teams to develop scalable AI applications and integrate AI capabilities into enterprise platforms. The role focuses on Python, Machine Learning, Generative AI, LLMs, RAG, APIs, and AWS, with particular emphasis on practical LLM and prompt-engineering experience using Claude and Kiro.

What You'll Do Develop and implement AI/ML solutions. Build Generative AI applications using Large Language Models (LLMs), including Kiro or Claude. Develop RAG-based applications using document processing, embeddings, vector databases, and semantic search. Integrate LLMs such as OpenAI and AWS Bedrock or equivalent platforms. Develop AI-powered chatbots, virtual assistants, document summarization, classification, extraction, and knowledge-management solutions. Implement prompt engineering techniques and evaluate LLM responses for accuracy, relevance, and reliability.

Build and integrate REST APIs and microservices to expose AI capabilities to enterprise applications. Work with structured and unstructured data and develop data-preparation and processing pipelines. Implement AI solutions using cloud services on AWS. Collaborate with senior engineers and architects to develop scalable and production-ready solutions. Participate in proof-of-concepts and rapidly evaluate emerging AI technologies. Develop unit tests, integration tests, and automated validation for AI applications.

Monitor AI applications and troubleshoot performance, accuracy, and production issues. Follow enterprise standards for security, data privacy, responsible AI, and application development. Contribute to technical documentation, solution design, and knowledge-sharing activities. Manage a team of offshore AI Engineers.

Required Qualifications 6–8 years of experience in software engineering, AI/ML, data science, or a related technology field.

Experience with Machine Learning and/or Generative AI applications. Practical experience working with LLMs and prompt engineering, including Claude and Kiro. Experience building RAG applications using embeddings and vector search. Experience working with REST APIs and microservices. Familiarity with Git and CI/CD practices. Good understanding of software development lifecycle and Agile methodologies. Strong problem-solving and communication skills.

Preferred Qualifications Knowledge of AI agents and agentic workflows.

Experience with Docker and Kubernetes. Familiarity with MLOps/LLMOps concepts.

Experience with AI evaluation, guardrails, and responsible AI. Experience working with enterprise data or regulated industries such as banking, financial services, or insurance. 2+ years of hands-on experience with AI/ML or Generative AI, including leading a team. Technology Environment

Languages:

Python, SQL AI/ML:
Machine Learning, NLP, Generative AI, LLMs GenAI: RAG, Prompt Engineering, Embeddings, Vector Search, AI Agents Frameworks:
PyTorch, Tensor Flow, Scikit-learn, Lang Chain/Lang Graph Cloud:
Azure / AWS / Google Cloud LLM Platforms:
Azure OpenAI, OpenAI, AWS Bedrock, Google Vertex AI Data: SQL, No

SQL, Vector Databases, Document Stores Engineering: REST APIs, Microservices, Git, Docker, CI/CD What Makes HTC A Great Place To Build Your Future HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you’ll collaborate with experts, work alongside clients, and be part of high-performing teams driving success…