About the Role We are looking for a Senior AI Engineer to design, build, and deploy production-ready AI solutions that solve real business problems and create measurable value. You will work across Generative AI, LLMs, RAG, AI agents, and machine learning, taking solutions from initial concept and proof of concept through production and continuous improvement. The role combines strong software engineering with practical AI expertise and requires close collaboration with business stakeholders, software engineers, data engineers, and product teams.
Key Responsibilities
Design and build production-ready AI solutions using LLMs, RAG, AI agents, and machine learning.
Translate business problems into practical AI solutions, selecting the right approach across AI, automation, analytics, and traditional software engineering.
Develop RAG pipelines, including embeddings, vector search, retrieval, and response evaluation.
Build AI agents and agentic workflows using tool/function calling, orchestration, and API integrations.
Evaluate and optimize models and AI applications for quality, reliability, latency, scalability, and cost.
Integrate AI solutions with enterprise applications, APIs, databases, ERP systems, and internal platforms.
Deploy and operate AI solutions in production, including monitoring, observability, versioning, and continuous improvement.
Establish evaluation, validation, and guardrail mechanisms to improve AI accuracy, reliability, and responsible use.
Work closely with technical and non-technical stakeholders to communicate AI capabilities, limitations, and technical trade-offs.
Contribute to AI architecture standards, engineering best practices, and technical guidance for other team members.
Required Skills
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field.
5+ years of software engineering or related technical experience, with at least 2–3 years of hands-on experience building and deploying AI/ML solutions.
Strong programming skills in Python and experience developing production-grade applications and APIs.
Hands-on experience with LLMs, Generative AI, prompt engineering, and RAG.
Practical experience with embeddings, vector databases, and semantic search.
Experience building AI agents, tool/function calling, or agentic workflows.
Strong understanding of machine learning and deep learning concepts and model evaluation.
Experience deploying AI applications to production and understanding MLOps/LLMOps, monitoring, and observability.
Experience working with SQL, APIs, Docker, Linux, and modern software development practices.
Strong analytical and problem-solving skills.
Excellent communication skills and the ability to explain technical concepts to non-technical stakeholders.
Good written and spoken English.
Preferred Skills
Experience with LangChain, LangGraph, LlamaIndex, or equivalent frameworks.
Experience with PyTorch, TensorFlow, Hugging Face, or similar ML frameworks.
Experience with cloud AI platforms such as Azure, AWS, or Google Cloud.
Experience with Kubernetes, CI/CD, MLflow, or other MLOps tools.
Experience with model fine-tuning, LoRA/PEFT, or inference optimization.
Experience integrating AI with ERP, enterprise applications, or internal business systems.
Experience mentoring engineers or providing technical leadership.
A portfolio of production AI projects, GitHub repositories, or relevant case studies is an advantage.