We are looking for a Senior AI Engineer to design, develop, and deploy scalable AI solutions using Large Language Models (LLMs), Generative AI frameworks, and modern cloud technologies.

The role involves building AI-powered applications using OpenAI, Gemini, GPT models, Python, FastAPI, PostgreSQL, and Google Cloud Platform (GCP).

The ideal candidate should have strong experience in AI model integration, backend development, RAG-based solutions, prompt engineering, and deploying production-grade AI systems.

Key Responsibilities:

- Design and develop AI solutions using LLMs, Generative AI, and modern AI frameworks.

- Integrate and optimize AI models including OpenAI, Gemini, and GPT-4.

- Develop Retrieval-Augmented Generation (RAG) pipelines and structured prompt engineering solutions.

- Build scalable APIs and microservices using Python, FastAPI, and FastMCP.

- Design and optimize PostgreSQL databases for AI applications.

- Develop secure data pipelines for AI training and inference workflows.

- Deploy and manage AI workloads on Google Cloud Platform (GCP), including Vertex AI.

- Implement testing, monitoring, security, and reliability practices for AI systems.

- Collaborate with product, engineering, and research teams to deliver enterprise AI solutions.

- Participate in Agile development practices including sprint planning, reviews, and retrospectives.

- Support production issue analysis, troubleshooting, and root cause resolution.

Required Skills & Qualifications:

- 5+ years of experience in AI/ML Engineering or related roles.

- Strong hands-on experience with OpenAI, Gemini, GPT-3.5, GPT-4, Python programming, FastAPI and backend development, YAML and API integrations, and PostgreSQL database design and optimization.

Experience with:

- RAG (Retrieval-Augmented Generation)

- Prompt Engineering

- PydanticAI / FastMCP

- MLOps and CI/CD practices

- Cloud deployment on GCP

Preferred Skills:

- Experience with LangChain or similar AI orchestration frameworks.

- Knowledge of AI safety, governance, and responsible AI practices.

- Experience with Docker/Kubernetes for AI workloads.

- Understanding of full-stack application development.

- Strong knowledge of software design, architecture, and implementation practices.

Core Competencies:

- Strong problem-solving and analytical skills.

- Ability to design scalable, secure, and high-performance solutions.

- Understanding of software engineering best practices.

- Experience working in Agile and CI/CD environments.

- Ability to collaborate effectively with cross-functional teams.

- Continuous learning mindset with awareness of emerging AI technologies.