Overview

AI/ML Engineer Job Summary

Responsibilities

• Design, develop, and deploy scalable AI/ML and Generative AI solutions for complex business problems.
• Develop production-grade applications using Python and frameworks such as FastAPI or Flask.
• Build and integrate LLM-based applications, RAG pipelines, and AI-powered solutions.
• Design RAG architectures covering document ingestion, chunking, embedding generation, retrieval, ranking, and response synthesis.
• Work with frameworks such as LangChain, LlamaIndex, or custom RAG implementations.
• Develop AI/ML solutions using AWS services including Amazon Bedrock, SageMaker, Lambda, API Gateway, and S3.
• Design and implement integrations with vector databases such as Pinecone, FAISS, or OpenSearch.
• Apply prompt engineering, embeddings, model evaluation, and performance optimization techniques.
• Develop secure APIs and implement OAuth 2.0, AWS IAM, authentication, authorization, and data protection mechanisms.
• Build and maintain CI/CD pipelines and follow DevOps practices using Docker, Terraform, CloudFormation, or AWS CDK.
• Work with relational databases, SQL, and data modelling for AI/ML applications.
• Perform data preprocessing, feature engineering, data manipulation, and model evaluation.
• Apply machine learning and deep learning algorithms to solve business problems.
• Own the complete AI/ML lifecycle, including requirements analysis, development, testing, deployment, monitoring, optimization, and production support.
• Use AI-assisted development tools such as GitHub Copilot to improve productivity, code quality, testing, and documentation.
• Ensure responsible AI practices, including validation of AI-generated outputs, secure coding, data privacy, explainability, and compliance with enterprise standards.
• Troubleshoot production issues, perform root-cause analysis, and optimize application and model performance.
• Collaborate with cross-functional and Agile teams to deliver AI/ML products successfully.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related technical field.
• 10+ years of overall software development experience.
• 3+ years of hands-on experience in Machine Learning, AI, or Generative AI application development.
• Strong proficiency in Python.
• Hands-on experience developing APIs using FastAPI or Flask.
• Strong experience with AWS cloud services, particularly:
• Amazon Bedrock
• Amazon SageMaker
• AWS Lambda
• API Gateway
• Amazon S3
• Strong practical experience with Generative AI and Large Language Models (LLMs).
• Hands-on experience with RAG architectures and LLM application development.
• Strong understanding of:
• Text embeddings
• Document chunking
• Vector search
• Retrieval and ranking
• Prompt engineering
• Response generation and evaluation
• Strong understanding of Machine Learning algorithms and Deep Learning architectures.
• Strong knowledge of SQL and relational databases.
• Understanding of cloud security, OAuth 2.0, IAM policies, secure API design, and data protection.
• Backend development experience in C# or Java is an added advantage.
• Proven experience delivering production-grade AI/ML solutions.
• Strong analytical and problem-solving abilities.
• Ability to translate complex business requirements into practical AI/ML solutions.
• Excellent communication skills with both technical and non-technical stakeholders.
• Ability to explain AI/ML concepts, model outcomes, and solution approaches clearly.
• Strong collaboration skills in cross-functional and Agile environments.

Education

• Digital consulting and transformation solutions
• Comprehensive staffing services (contract, temporary, permanent placements)
• Talent management and workforce solutions
• Technology implementation services
• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related technical discipline.