Location - Jersey City NJJob Description We are seeking a highly skilled Forward Deployed Engineer with expertise in Full Stack Java Development, AI/ML Engineering, and Generative AI solutions. This role combines software engineering, data engineering, and AI solution development to solve complex business challenges. The ideal candidate will work closely with business stakeholders, operations teams, and subject matter experts to design, build, deploy, and scale production-grade AI-powered applications and intelligent automation solutions.
As a Forward Deployed Engineer, you will rapidly prototype innovative solutions, integrate AI capabilities into enterprise ecosystems, and transform successful outcomes into reusable platform services that drive business value at scale.
Key Responsibilities- Design, develop, and deploy production-grade AI/ML solutions leveraging Traditional ML, LLMs, Agentic AI, RAG, and workflow automation frameworks.
- Build scalable backend services, APIs, and microservices using Java/Python, MongoDB, Kafka, and event-driven architectures.
- Develop intelligent AI agents using tool calling, MCP, prompt engineering, context management, guardrails, and evaluation frameworks.
- Integrate AI solutions with enterprise applications, business workflows, APIs, and data platforms to drive operational outcomes.
- Analyze operational and historical data using SQL, Spark, and Databricks to identify root causes and implement data-driven solutions.
- Collaborate with Operations teams and business stakeholders to rapidly prototype, deploy, measure impact, and scale AI-powered solutions.
Required Skills & Qualifications- 8 to 10 years of experience in Software Engineering, Machine Learning, Data Engineering, or related domains.
- 3 to 5 years of hands-on experience designing and deploying Agentic AI and Generative AI solutions.
- Strong proficiency in Java and/or Python with experience in REST APIs, microservices, and distributed systems.
- Hands-on experience with LLMs, AI Agents, RAG architectures, prompt engineering, and AI evaluation frameworks.
- Experience working with MongoDB, Kafka, event-driven architectures, and enterprise-scale applications.
- Strong SQL and data engineering expertise, including Spark and Databricks.
- Proven experience deploying, monitoring, and supporting production AI/ML solutions at enterprise scale.
- Excellent problem-solving, stakeholder management, communication, and customer-facing solution engineering skills.
The base compensation range for this role in the posted location is: $100,000.00 - $130,000.00
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
