AI Platform Engineer

Capgemini; Atlanta (GA); On-site; USD 129,000 - 143,000; Full time

Benefits offered by this job

Paid time off

Medical/Dental/Vision coverage

Retirement plans (401k)

Job summary

Capgemini is hiring an AI Platform Engineer in Atlanta to own platform components end-to-end, including model gateway, agent runtime, and evaluation harness. You will architect training/adaptation pipelines and guardrail systems while focusing on reliability, latency, and cost efficiency of platform services.

The role emphasizes building self-service surfaces and close collaboration with product teams, embedding services in product lines before scaling to platform.

Qualifications

• Strong production engineering: Python and a systems language (Go or Rust) with Kubernetes, IaC, and one major cloud.
• Hands-on experience with LLM infrastructure: model gateway patterns, model serving, and vector/retrieval systems.
• Agent-systems experience: built with an agent orchestration framework and MCP.
• Evaluation engineering: built or operated eval harnesses and CI gates for LLMs.
• Post-training fluency: fine-tuned or post-trained models and data pipelines in production.
• Daily, hands-on use of AI coding assistants in development workflows.

Responsibilities

• Own platform components end-to-end including model gateway, agent runtime, evaluation harness, and guardrail engine.
• Build training/adaptation pipelines from production traces to RL and fine-tuning datasets.
• Ensure reliability, latency, and cost efficiency of platform services.
• Create self-service surfaces with documentation and sane defaults.
• Co-build with product teams; embed services in a product line before scaling to platform.

Skills

Python

Go or Rust

Kubernetes

Infrastructure as Code

Cloud platforms

LLM infrastructure

Model gateway

Model serving

Evaluation harness

Retrieval systems

Agent orchestration framework

MCP

LangSmith

LangGraph

PostgreSQL with pgvector

ClickHouse

S3

OpenTelemetry

Grafana

Helm

Argo CD

Tools

LangSmith platform

LangGraph platform

PostgreSQL with pgvector

ClickHouse

S3-compatible storage

Neo4j Enterprise

OpenTelemetry

Grafana

Kubernetes cluster

Helm

Argo CD

Job description

# AI Platform EngineerAtlantaApply for this job* Permanent* Experienced Professionals* Portfolio & Product Management* ID 585389-en\\_USChoosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.## **What you will own**One or more platform components end to end: model gateway (routing, failover, caching, per-line cost attribution), agent runtime and orchestration, evaluation harness, guardrail engine, tool and agent registry, or shared product servicesThe training and adaptation loop: pipelines that turn production traces and evaluation verdicts into reinforcement learning and fine-tuning datasets, and the infrastructure to train, evaluate, and serve NewCo-tuned LLMs and SLMs behind the same gates as vendor models Reliability, latency, and cost of what you build; platform services carry baselines and you hold them The self-service surfaces product engineers use: your components ship with documentation, sane defaults, and no ticket queue Co-building with product teams: new shared services start embedded with a product line and graduate to platform services when proven## **What you will need**Strong production engineering: Python plus one systems language (Go or Rust welcome), Kubernetes, infrastructure-as-code, and one major cloud Hands-on experience with LLM infrastructure: a model gateway pattern (such as LiteLLM or in-house), model serving (such as vLLM or managed endpoints), and vector or retrieval systems Agent-systems experience: you have built with an agent orchestration framework (such as LangGraph or first-party agent SDKs) and understand tool calling and the Model Context Protocol (MCP) Evaluation engineering: you have built or operated eval harnesses (golden datasets, regression gates in CI, LLM-judge calibration) and can explain why they gate merges Post-training fluency: you have fine-tuned or post-trained a model, built the data pipeline behind one, or reproduced techniques from recent papers in production systems Daily, hands-on use of AI coding assistants as part of your own development workflow We care about depth in four or five of these areas more than surface familiarity with all of them.What sets you apart Guardrail-engine or AI-observability experience (NeMo Guardrails, OpenTelemetry GenAI conventions, LangSmith, Braintrust, or equivalent) Reinforcement learning infrastructure (reward modelling, RLHF or GRPO-class pipelines) or SLM distillation experience Multi-tenant SaaS infrastructure: tenancy isolation, metering, usage-based billing Financial services engineering (banks, insurers, or payment providers) is the ideal background; other regulated-industry or security engineering depth also counts Open-source contributions or a portfolio of deployed agents and eval suites (we would rather see this than a CV)The reference stack The reference technology stack for this role is our supported paved road: self-hosted LangSmith and LangGraph Platform as the agent runtime and evaluation plane, model providers behind a swappable gateway seam, PostgreSQL with pgvector plus ClickHouse and S3-compatible object storage as the data platform, Neo4j Enterprise as the semantic knowledge graph, an agent memory plane serving episodic and precedent memory over MCP, MCP-native connectors, OpenTelemetry and Grafana for observability, all on CNCF-conformant Kubernetes with Helm and Argo CD, deployable to any hyperscaler or on-prem. A tool-for-tool match is not expected: analogous experience counts fully. If you have built and operated systems of this shape on comparable components (a different orchestration framework, graph engine, evaluation platform, or serving stack), you have what we are looking for.## **How we work**Engineers write specs, harnesses, evals, and guardrails; AI agents execute the implementation loops. Review, not typing, is where engineering judgment goes. Three human gates govern everything we ship: spec approval, merge, and release. Regulated code paths (money movement, authentication, cryptography, secrets) are always human owned. Small and senior by design. No separate QA function, no scrum masters; quality .The base compensation range for this role in the posted location is: 129,000 to 143,000.Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.It is not typical for candidates to be hired at or near the top of the posted compensation range.In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.**Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees.** In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: * Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave* Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)* Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)* Life and disability insurance* Employee assistance programs* Other benefits as provided by local policy and eligibility**Important Notice:** Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.**Disclaimers**Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.Please be aware that Capgemini may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process.Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-lawCapgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.