Managing Solution Architect

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Your Role

We are seeking a highly technical, hands-on, and implementation-focused Solution Architect for Cloud, Data Analytics and AI In this role, your primary focus will be implementation and end-to-end technical execution. You will be the solution architect, designing architecture blueprints suggesting right fit technologies for solving complex technical asls from clients in areas of Data, Cloud and AI. You will be guiding team to write code, build prototypes, and directly guiding development teams to turn complex system designs into stable, scalable production grade solutions.

Key Responsibilities

• •Drive the day-to-day coding, technical builds, and engineering delivery of end-to-end data and AI platforms, working closely with Capgemini’s development team and clients .
• •Partner directly with client delivery teams to execute complex platform migrations, cloud migrations, and tech-stack modernization projects across Data, Analytics, and AI domains. Hands on Knowledge of Gen AI is must. The candidate must be able to use Claude Code, Open AI Codex and Cursor.
• •Build, scale, and realize detailed enterprise blueprints, translating conceptual patterns like Data Lake Medallion, event-driven, domain-driven, and modular microservices into functional application stacks.
• •Support presales activities by creating rapid technical prototypes, conducting proof-of-concept (POC) builds, and architecting specific implementation pricing engines based on deep technical realities are required.
• •Collaborate directly with technical leads from our alliance ecosystem-such as AWS, Microsoft, Google, Snowflake, Databricks, and Anthropic to know their latest features.
• •Lead sprint teams from an engineering perspective, taking full ownership of deployment pipelines, complex environment configurations, and the real-time resolution of critical blockages during development phases.

Required Skills and Expereince

• •Minimum of 14 years of experience in the IT industry.
• •Minimum of 6 years of dedicated experience acting in an Architecture capacity.
• •Industry awareness across one or more sectors is highly valued: Manufacturing, Automotive, Life Sciences, Telecommunications, Media, Hi-Tech, or Energy & Utilities.
• •Bachelor’s or master’s degree in computer science, Information Systems, or a closely related technology field

Technical Skills & Competencies

• •Expert-level, hands-on programming proficiency in Spark, Scala, and Java within major hyperscaler environments (AWS, Azure, or Google Cloud). Active, professional cloud certifications are highly desired.
• •Deep practical implementation experience with AI ecosystems like AWS Bedrock, AWS SageMaker, Google Vertex AI, Azure ML, and OpenAI. Mastery of building functional pipelines featuring prompt engineering, LLM fine-tuning, Agent Mesh, RAG, Vector Databases, Chain-of-Thought, Context Engineering, Loop Engineering, and MLOps/LLMOps. Direct facility with AI developer productivity toolsets (e.g., Cursor, Codex, Claude Code). While vibe coding knowledge is good to have, hands on implementation knowledge of LLM fine tuning, context engineering, Vector Databases Design, Model Routing, LLM Orchestration, Developing Agents and building Agentic Mesh, technologies such as LangChain, LlamaIndex, PineCone, Milvus, PyTorch, Tensor Flow and different transformer models including Claude, Gemini, OpenAI models, and ability to optimize token usage etc. are crucial for this role.
• •Strong data engineering experience with cross-platform analytical data warehouses and data lakes houses, specifically Python, Spark, Big Query, Redshift, Synapse, Databricks or Snowflake.
• •The candidate should have exposure to different styles of database modeling relational systems and modern NoSQL databases. Exposure or working knowledge in Graph database will be valuable.
• •Experience in developing microservices, event-driven platforms, and streaming/batch pipelines (Glue, Data Factory, DataFlow, Composer, Airflow, Kafka, Flink, or equivalent cloud services).
• •Experience in Data Governance tools for data quality, data lineage, observability, and data marshalling, with preference for practical tooling validation using Informatica, Alation, Collibra, or Reltio will be valuable.
• •Direct experience structuring real-world semantic layers, creating reusable data products, managing secure data shares, will be valuable.
• •Awareness about secure network layout, infrastructure security controls, fault-tolerant/resilient cloud architecture setups, and FinOps scripting for resource scaling and cost optimization will be valuable.
• •Deep fluency in DataOps, DevOps, and delivery pipeline automation, with direct hands-on configuration experience using GitHub Actions, Jenkins, Terraform, and git version management within fast-paced Agile environments are required

The base compensation range for this role in the posted location is $150,000- $220,000

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 w