Overview
Skills
Job Details
Location: Culver City, CA / Sunnyvale, CA / Austin, TX (Hybrid 3 Days Onsite, 2 Days Remote)
Duration: 6 12 Months
Rate: $70/hr on C2C
Client: Confidential
We are seeking a Senior Full Stack Engineer to join the Services Technology Organization, focusing on building and deploying AI-driven solutions with a strong emphasis on secure systems integration. This role requires a seasoned backend engineer with a deep understanding of enterprise system connectivity, authentication frameworks, and scalable service design.
This is not an AI/ML engineer role-the primary focus is system integration for AI solutions, ensuring secure, efficient connections between multiple enterprise platforms and AI services.
Key Responsibilities:-
Design, develop, and maintain robust backend and frontend systems that integrate AI capabilities across enterprise platforms.
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Implement secure authentication and authorization mechanisms across multiple systems (OAuth, IAM).
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Integrate internal and third-party systems via REST and Graph APIs to enable AI interactions.
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Collaborate with cross-functional teams to deploy AI-based services and ensure smooth system interoperability.
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Manage Kubernetes-based deployments and CI/CD pipelines using GitHub.
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Design secure, scalable, and maintainable microservices architectures.
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Navigate complex organizational structures and coordinate with multiple stakeholders to deliver end-to-end solutions.
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5 10+ years of strong backend and full stack development experience.
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Proficiency in Python (primary), Java, and JavaScript.
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Experience developing and maintaining REST APIs, Graph APIs, and microservices.
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Deep expertise in Identity and Access Management (IAM) and OAuth authentication.
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Hands-on experience with Kubernetes (AI services run on K8s).
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Strong understanding of CI/CD processes with GitHub (configuration-level experience).
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Proven ability to work autonomously and handle cross-functional coordination in complex enterprise environments.
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Experience implementing Model Context Protocol (MCP) servers.
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Familiarity with AI/ML solution integration or deployment.
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Prior experience with large-scale, distributed system architecture.
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Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent experience).