Artificial Intelligence Engineer

Own the design, development, deployment, and quality of AI agents on AWS using Amazon Bedrock foundation models and Amazon Bedrock AgentCore. This hands-on engineering role requires direct experience building and deploying agents-not solely prompt design or the use of AI coding assistants. Work with client developers to establish a reusable reference implementation, deliver a five-template agent pilot, and transfer secure, testable engineering patterns that the client can sustain., * Design and implement agents using Amazon Bedrock models and deploy them through AgentCore Runtime, using Strands Agents, LangGraph, or an appropriate custom framework.

• Configure each agent archetype’s instructions, context, tool definitions, orchestration, session handling, and structured result contracts; implement AgentCore Memory where persistent context is required.
• Connect agents to enterprise APIs, AWS Lambda functions, and MCP tools using AgentCore Gateway and Model Context Protocol integrations as appropriate.
• Implement least-privilege IAM permissions, secure credential handling, and agent authentication and authorization, using AgentCore Identity where appropriate.
• Build the first golden agent template as the reference implementation for the other four, including configuration, deployment automation, documentation, and reusable integration patterns.
• Build output verification, path and tool allowlists, schema validation, API contract tests, automated agent evaluations, and review-ready pull request structures. Define human approval points for sensitive actions.
• Instrument agents using AgentCore Observability and Amazon CloudWatch to troubleshoot execution, tool calls, errors, latency, and token consumption.
• Run the pilot tuning loop: analyze failures, evaluation results, and reviewer feedback; improve prompts, context, tools, templates, and model configuration against agreed acceptance criteria.
• Automate repeatable AWS deployments with infrastructure as code and CI/CD; document environment configuration, operational procedures, and rollback approaches.
• Pair with the client’s API developer on templates 2 through 5 and transfer architecture, testing, troubleshooting, and operational knowledge.

Success Criteria:

• A working golden agent template deployed to the agreed AWS environment using AgentCore Runtime and Amazon Bedrock models.
• Five reusable agent templates delivered with the client team, with documented configurations, tool interfaces, result contracts, and deployment instructions.
• An automated verification and evaluation suite, with acceptance criteria and baseline measures for task success, output quality, latency, and token consumption agreed with the client.
• Documented security controls, operational monitoring, troubleshooting guidance, and knowledge transfer enabling client developers to extend and maintain the agents.

• 5+ years building production APIs on AWS, including REST and at least one of GraphQL or event-driven architectures.
• Demonstrated hands-on experience developing and deploying AI agents using Amazon Bedrock models and Amazon Bedrock AgentCore, including direct implementation experience with AgentCore Runtime.
• Hands-on experience with at least one additional AgentCore capability: Gateway, Memory, Identity, or Observability. General familiarity with Bedrock or use of coding assistants alone does not satisfy the AgentCore requirement.
• Strong Python and/or TypeScript development skills, AWS SDK experience, and experience implementing agent orchestration and tool calling with an agent framework or custom code.
• Experience integrating agents with enterprise APIs and tools, including MCP-based integrations or AgentCore Gateway.
• Practical AWS engineering skills with IAM, Lambda, API Gateway, CloudWatch, and services such as S3 or DynamoDB; ability to implement secure access and troubleshoot distributed applications.
• Strong testing discipline: OpenAPI, unit and integration testing, contract tests, structured-output validation, and automated evaluation of agent behavior and generated code.
• Experience with Git, pull request workflows, CI/CD, and infrastructure as code using AWS CDK, AWS CloudFormation, or Terraform.
• Ability to explain agent architecture, security controls, behavior, and failure modes clearly, and to pair effectively with client engineering teams.

What you will bring (Preferred):

• Experience operating AgentCore-based agents in production, including incident troubleshooting, performance tuning, and cost optimization.
• Experience across multiple AgentCore capabilities, including Memory, Identity, Gateway, and Observability.
• Experience with Amazon Bedrock Knowledge Bases, retrieval-augmented generation, and Amazon Bedrock Guardrails.
• Experience building MCP servers, multi-agent workflows, or agent-to-agent integrations.
• Built reusable templates, scaffolding, or code generators adopted by other engineering teams; measured acceptance rates and compared agent configurations.
• Hands-on use of Kiro, Claude Code, or similar coding agents in specification-driven or headless workflows beyond IDE autocomplete.
• Experience with BMAD or similar specification-driven development methods.

Life at Sogeti: Sogeti supports all aspects of your well-being throughout the changing stages of your life and career. For eligible employees, we offer:

• Flexible work options
• 401(k) with 150% match up to 6%
• Employee Share Ownership Plan
• Medical, Prescription, Dental & Vision Insurance
• Life Insurance
• 100% Company-Paid Mobile Phone Plan
• 3 Weeks PTO + 7 Paid Holidays
• Paid Parental Leave
• Adoption, Surrogacy & Cryopreservation Assistance
• Subsidized Back-up Child/Elder Care & Tutoring
• Career Planning & Coaching
• $5,250 Tuition Reimbursement & 20,000+ Online Courses
• Employee Resource Groups
• Counseling & Support for Physical, Financial, Emotional & Spiritual Well-being
• Disaster Relief Programs, Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future. The disclosed range takes into account the wide range of factors that are considered in making compensation decisions including, but not limited to, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, performance, sales or revenue-based metrics, and business or organizational needs. At Capgemini, it is not typical for an individual to be hired at or near the top of the range for their role. The base salary range for this role is located in the job posting. This role may be eligible for other compensation including variable compensation, bonus, or commission. Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees. xrbllit

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company’s sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law.

Part of the Capgemini Group, Sogeti makes business value through technology for organizations that need to implement innovation at speed and want a local partner with global scale. With a hands-on culture and close proximity to its clients, Sogeti implements solutions that will help organizations work faster, better, and smarter. By combining its agility and speed of implementation through a DevOps approach, Sogeti delivers innovative solutions in quality engineering, cloud and application development, all driven by AI, data and automation.