Job Location

Job is located in McLean-VA - Onsite Hybrid

Your Role

Responsibilities:

Design build and own end-to-end software solutions across the full development lifecycle from architecture to production
Develop scalable backend systems and data pipelines using Scala
Serve as an internal enabler of AIled development onboarding the team onto agentic tools like Claude Cursor Windsurf
Identify and drive productivity acceleration opportunities across the engineering team using AI coding workflows
Mentor engineers and set best practices for AI augmented software delivery
Collaborate with product and application teams to ship high-quality features iteratively8-12 years of end-to-end software development experience covering design build test deploy and operate
Proven track record of delivering production grade systems at scale ideally across multiple domains or industries
Experience working in Agile Scrum environments with cross functional teams
Comfortable owning technical decisions independently and presenting solutions to engineering leadership

Engineering depth

5 years of hands-on Scala development strong grasp of functional programming type systems and the JVM ecosystem
Solid understanding of distributed systems system design and software architecture patterns microservices eventdriven CQRS
Experience with test driven development TDD code review practices and CICD pipelines
Familiarity with data modelling ETLELT pipelines and working with largescale datasets

AI tooling productivity

Hands on experience using Claude Anthropic for AI assisted development code generation and problem-solving
Ability to evaluate adopt and champion emerging AI coding tools as the landscape evolves
Experience measuring and articulating productivity gains from AI tooling adoption across a team

Technical skills

Languages frameworks

Scala Akka Cats Cats Effect ZIO Play Framework SBT
SQL advanced query writing query optimization schema design

AI LLM tooling

Claude Anthropic API prompt engineering API integration agentic workflows
Cursor AInative IDE multifile editing agent mode
Windsurf Cascade agentic workflows AIdriven code navigation
LLM application development LangChain LlamaIndex RAG pipelines vector databases Pinecone Weaviate pgvector
Familiarity with OpenAI Gemini or other LLM provider APIs

Cloud infrastructure

Cloud platforms AWS S3 EC2 ECS Lambda Kinesis RDS GCP or Azure
Containerization Docker Kubernetes Helm
CICD GitHub Actions Jenkins GitLab CI ArgoCD
Infrastructure as Code Terraform Pulumi

Observability quality

Monitoring and logging Datadog Grafana Prometheus ELK Stack
Testing unit integration contract testing ScalaTest Test containers
Code quality SonarQube linting static analysis

Nice to have

Experience with LLM application development RAG pipelines prompt engineering or LangChain LlamaIndex
Background in data engineering or platform engineering at scale
Prior experience as a technical lead or engineering mentor
Familiarity with functional programming principles Cats Cats Effect ZIO

The base compensation range for this role in the posted location is: 80420 - 106050

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