Sr AI Engineer

Job highlights

• Required Qualifications: 5+ years in AI / ML engineering or related roles
• Hands-on experience with OpenAI,Gemini,and GPT,5,GPT-. Strong proficiency in Python,YAML and frameworks like FastAPI
• Cloud deployment experience on GCP
• Experience with LangChain or similar orchestration frameworks

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.

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.

Required Qualifications:

5+ years in AI/ML engineering or related roles.

Hands-on experience with OpenAI, Gemini, and GPT, 3.5, GPT-4.0.

Strong proficiency in Python, YAML and frameworks like FastAPI.

Familiarity with PydanticAI and FastMCP for structured AI development.

Skills:

Database design and optimization in PostgreSQL.

Cloud deployment experience on GCP.

Understanding of MLOps and CI/CD for AI systems.

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

Competencies and Best Practice for High Performers

Software Engineering:

Applies coding skills to defined capabilities or tasks as assigned with little guidance, becomes go-to for development of some capabilities or functions

Demonstrates an automation first mentality that improves quality and efficiency

Develops understanding of cost, complexity, and capability tradeoffs in underlying architectures

Develops awareness of upstream and downstream system interactions and dependencies

Instruments features delivered using team- and/or product-standard monitoring and diagnostic frameworks

Reuses and or develops for reuse code algorithms, or data structures to address common needs

Actively follows industry trends in technology, tools, and components, sharing findings with team members

Participates in Agile and CI-CD (Continuous Integration and Continuous Deployment) practices, takes ownership of some processes or practices for team

Has awareness of the operational characteristics (i.e., security, performance, scalability, manageability) of solutions and is accountable for supporting those requirements in contributed code

Customer Centric/Design Thinking:

Contributes to increasing team understanding of user perspective and values while advocating for user needs

Understands what creates business or market impact and how design and delivery activities are related to that impact

Participates in development of prototypes (mockups, models, simulations, functional capabilities) to support user engagement, interaction, and feedback

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.