Managing Solution Architect

Uses Cursor and AI assistants; mentions vibe coding as a plus and emphasizes hands‑on Gen AI/LLM tooling.

Capgemini is hiring a hands‑on Managing Solution Architect to design and implement end‑to‑end cloud, data analytics, and AI platforms. The role focuses on technical leadership: coding, building prototypes, guiding development teams, and delivering production‑grade, scalable AI and data solutions.

Managing Solution Architect focused on Cloud, Data Analytics, and AI. This is a highly technical, implementation‑focused position responsible for designing architecture blueprints, selecting appropriate technologies, driving hands‑on development, and guiding teams to deliver production‑grade solutions.

• Lead day‑to‑day coding, technical builds, and engineering delivery for end‑to‑end data and AI platforms.
• Partner with client delivery teams to execute complex platform and cloud migrations, and tech‑stack modernization projects.
• Build and scale enterprise blueprints (e.g., Data Lake Medallion, event‑driven, domain‑driven, microservices) into functional application stacks.
• Create rapid technical prototypes and proof‑of‑concepts to support presales activities.
• Collaborate with technology alliance partners (AWS, Microsoft, Google, Snowflake, Databricks, Anthropic) to leverage platform features.
• Lead sprint teams from an engineering perspective, own deployment pipelines, environment configuration, and resolve critical development blockages.

• Minimum 14 years of IT industry experience and at least 6 years in an architecture capacity.
• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• Industry awareness across sectors such as Manufacturing, Automotive, Life Sciences, Telecommunications, Media, Hi‑Tech, or Energy & Utilities is valued.
• Expert, hands‑on programming with Spark, Scala, and Java in major hyperscaler environments (AWS, Azure, Google Cloud); professional cloud certifications preferred.
• Practical implementation experience with AI platforms and ecosystems such as AWS Bedrock, AWS Sage Maker, Google Vertex AI, Azure ML, and OpenAI.
• Deep knowledge of LLM workflows: prompt engineering, fine‑tuning, RAG, vector databases, agent architectures/Agent Mesh, model routing, orchestration, and related MLOps/LLMOps practices.
• Familiarity with AI developer productivity tools (e.g., Cursor, Codex, Claude Code) and technologies like Lang Chain, Llama Index, Pinecone, Milvus, PyTorch, Tensor Flow, and transformer models (Claude, Gemini, OpenAI models).
• Strong data engineering experience with Python, Spark, Big Query, Redshift, Synapse, Databricks, Snowflake, and experience with streaming/batch platforms (Glue, Data Factory, Data Flow, Composer, Airflow, Kafka, Flink).
• Experience with data governance tooling (Informatica, Alation, Collibra, Reltio), semantic layers, reusable data products, and secure data sharing.
• Hands‑on experience with Dev Ops and delivery automation:
  Git Hub Actions, Jenkins, Terraform, and git; familiarity with Fin Ops, infrastructure security, and resilient cloud architecture.
• Base compensation range: $150,000 - $220,000 (base for the posted location).
• Role may be eligible for additional variable incentives, bonuses, or commissions depending on position and local laws.
• Benefits (U.S. and Canada examples): paid time off by grade (vacation 12–25 days), company holidays, personal days, sick leave, medical/dental/vision coverage, retirement savings plans (e.g., 401(k), RRSP), life and disability insurance, employee assistance programs.

Solution Architecture System Design Hands‑on Coding Technical Leadership Team Leadership Presales and POC Development Cloud Migration Data Engineering MLOps/LLMOps Data Governance Dev Ops and CI/CD Agile Delivery Prototype Development Stakeholder Management Security & Fin Ops Awareness Streaming & Batch Pipeline Development

USD 150,/year

Full‑time

• Paid time off (vacation 12-25 days depending on grade)
• Company paid holidays
• Personal days
• Sick leave
• Medical coverage
• Dental coverage
• Retirement savings plans (e.g., 401(k), RRSP)
• Disability insurance
• Employee assistance programs