Artificial Intelligence Engineer

Factspan is a pure play data and analytics services organization. We partner with fortune 500 enterprises to build an analytics center of excellence, generating insights and solutions from raw data to solve business challenges, make strategic recommendations and implement new processes that help them succeed.With offices in Seattle, Washington and Bangalore, India;we use a global deliverymodel to serviceour customers. Our customers includeindustry leaders from Retail, Financial Services, Hospitality, and technology sectors. Key Responsibilities: Architect and implement robust backend services and microservices for AI Design APIs with scalability, reliability, and security in mind. Optimize system performance for high throughput and low latency. Integrate AI/ML models and LLM based applications into production systems Experience in building end to end Gen AI based applications/solutions Collaborate with data scientists to operationalize AI pipelines Implement features for model evaluation, monitoring, and feedback loops. DevOps & CI/CD Maintain automated pipelines for build, test, and deployment. Ensure compliance with code quality and security standards. Drive end-to-end design, building, and deployment of enhancements using Python, APIs, and Microservices. Scalability & Performance Design systems for horizontal scaling and fault tolerance. Conduct performance tuning and load testing to ensure optimal resource utilization. Foundational Services Build reusable frameworks and services that support multiple AI platform Implement secure handling of sensitive data (PHI/PII redaction) Database & Data Management Work extensively with No SQL databases (Mongo DB, Cosmos DB) Ensure efficient data ingestion and retrieval for AI-driven applications. Professional Qualifications: Must have good communication and interpersonal skills. Ability to guide the team and deliver as an Individual Contributor without much supervision. Required Skills: Strong SQL, Python, and Query Analysis skills are required for this role. Programming: frameworks, Java or Go for backend. Microservices architecture, RESTful APIs, distributed systems. Experience building data pipelines, APIs, and microservices. AI/ML Tools: TensorFlow, PyTorch, LangChain, Vertex AI, LLMs, and general Gen AI/Agentic AI experience. Agentic AI & Google ADK: Experience designing and implementing production-grade Agentic AI systems using Google ADK, including multi-agent workflows, tool-calling, and Model Control Plane (MCP) Server services (for exposing internal tools/APIs). Google ADK experience is highly preferred. GCP, Kubernetes, Docker. GCP experience is highly preferred. Databases: No SQL databases (Mongo DB, Cosmos DB), SQL, and Big Query experience are highly preferred. Performance Optimization: Profiling, caching strategies, query optimization, and the ability to identify performance bottlenecks and optimize performance using Gen AI. Observability experience. Other: Experience with design and support for multiple applications. #J-18808-Ljbffr