Senior AI Engineer

Experience: 5 to Not Available years

Location: Others, India

Skills: Python, OpenAI, Gemini, GPT-4.0, PydanticAI, FastAPI, FastMCP, PostgreSQL, Google Cloud Platform, Vertex AI, MLOps, CI/CD, YAML, LangChain, Docker, Kubernetes

Job Summary
The Senior AI Engineer will design, develop, and deploy advanced AI solutions leveraging large language models (LLMs) and contemporary frameworks. This role requires expertise in Python, OpenAI, Gemini, GPT-4.0, and emerging AI libraries such as PydanticAI, combined with strong backend development skills using FastAPI, FastMCP, and database technologies like PostgreSQL. The engineer will work on scalable AI systems hosted on Google Cloud Platform (GCP), ensuring performance, security, and compliance.

Major Responsibilities:
• Participate in creating solutions for functional and non-functional requirements
• Collaborate with the Scrum team in an agile development environment
• Contribute to continuous improvement of SDLC processes and methodologies
• Develop solutions with scalability and flexibility in mind
• Ensure development delivery meets expectations as defined in a User Story
• Attend and actively participate in all Sprint meetings (Refinement, Planning, Stand-up and Retrospective)
• Accountable to accept and deliver work within each sprint that closely matches planned capacity; escalate to Scrum Master and/or manager if there is an insufficient number of User Stories in the backlog to achieve this.
• Quickly identify roadblocks/impediments and escalate to the Tech Lead or Scrum Master
• When engaged by Operations,



assist with root cause analysis and resolution of production Incidents.
• AI Model Integration & Development
• Build and integrate LLM-based solutions using OpenAI, Gemini, and GPT-4.0.
• Implement structured prompt engineering and Retrieval-Augmented Generation (RAG) for context-aware responses.
• Backend Engineering
• Develop robust APIs and microservices using FastAPI and FastMCP.
• Ensure high-performance data flow between AI models and application layers.
• Data Management
• Design and optimize relational schemas in PostgreSQL for AI-driven applications.
• Implement secure data pipelines for training and inference.
• Cloud Deployment
• Architect and deploy AI workloads on GCP, leveraging Vertex AI and related services.
• Optimize infrastructure for scalability and cost efficiency.
• Quality & Reliability
• Apply best practices for testing, validation, and monitoring of AI systems.
• Ensure compliance with ethical AI principles, including fairness and transparency.
• Collaboration
• Partner with product, data engineering, and research teams to deliver enterprise-grade AI solutions.
• Mentor junior engineers and contribute to internal AI knowledge bases.





Preferred Qualifications:
• Experience with LangChain or similar orchestration frameworks.
• Knowledge of prompt engineering and AI safety practices.
• Familiarity with containerization (Docker/Kubernetes) for AI workloads.
• Demonstrated knowledge of application design, application development and implementation.
• Understanding basic full stack development concepts
• Excellent human relations skills to effectively interact with management, peers, business partners and vendors

Key Responsibilities
The Senior AI Engineer will design, develop, and deploy advanced AI solutions leveraging large language models (LLMs) and modern frameworks. This role requires expertise in Python, OpenAI, Gemini, GPT-4.0, and emerging AI libraries such as PydanticAI, combined with strong backend development skills using FastAPI, FastMCP, and database technologies like PostgreSQL. The engineer will work on scalable AI systems hosted on Google Cloud Platform (GCP), ensuring performance, security, and compliance.
Skill Requirements
Skills:
• Database design and optimization in PostgreSQL.
• Cloud deployment experience on GCP.
• Understanding of MLOps and CI/CD for AI systems.

Other Requirements
Required Qualifications:
• 5+ years in AI/ML engineering or related roles.
• Hands-on experience with OpenAI, Gemini, and GPT, 3.5, GPT-4.0.
• Solid proficiency in Python, YAML and frameworks like FastAPI.
• Familiarity with PydanticAI and FastMCP for structured AI development.

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