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Role OverviewCognizant is seeking an accomplished
Lead Full Stack AI Engineer to provide hands-on technical leadership in designing, developing, and deploying enterprise-scale AI solutions powered by AWS cloud technologies, Generative AI, and Agentic AI frameworks.
This role combines deep software engineering expertise with advanced AI solution architecture and cloud-native development. The successful candidate will lead the delivery of scalable, secure, reliable, and cost-optimized AI applications while driving engineering best practices and mentoring development teams.
The ideal candidate will possess strong experience building LLM-powered applications, Retrieval-Augmented Generation (RAG) solutions, agentic workflows, cloud-native architectures, and enterprise-scale AI platforms.
Work ModelThis position follows a
hybrid work model based in
New Jersey. Candidates local to New Jersey are strongly preferred and should be available to work onsite as required by client and business needs.
Key ResponsibilitiesAI Solution Architecture & Engineering- Lead the architecture, design, development, and production deployment of enterprise AI solutions spanning:
- Traditional Machine Learning
- Generative AI
- Agentic AI
- Design scalable, secure, and production-ready AI applications that align with enterprise architecture standards.
- Translate business requirements into technical architectures and implementation plans.
- Drive solution design decisions balancing scalability, maintainability, performance, security, and cost optimization.
Full Stack Application Development- Provide hands-on engineering leadership across:
- Front-End Applications
- Backend Services
- APIs
- Microservices
- AI Orchestration Layers
- Enterprise Integrations
- Develop modern user experiences using React or comparable front-end frameworks.
- Design robust backend services using Python, FastAPI, and cloud-native development practices.
- Build enterprise-grade distributed systems and event-driven architectures.
Generative AI & Agentic AI Solutions- Design and implement advanced AI solutions leveraging:
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Knowledge Management Platforms
- Enterprise Search Solutions
- Develop agentic workflows using:
- AWS Bedrock AgentCore
- LangGraph
- Strands Agents
- Modern AI Orchestration Frameworks
- Implement multi-agent systems supporting:
- Tool Calling
- MCP Integration
- Agent Memory
- State Management
- Workflow Orchestration
- Optimize AI solution performance, accuracy, reliability, and explainability.
Enterprise AI Platform Integration- Architect integrations with enterprise AI platform capabilities including:
- AI Gateway
- MCP Gateway
- Agent & Tool Registry
- Knowledge Management Platforms
- RAG Services
- Enterprise Search Services
- Agent Memory Frameworks
- Observability Platforms
- Ensure seamless integration across enterprise applications and AI ecosystems.
- Design reusable AI services and platform accelerators.
AWS Cloud Engineering- Leverage AWS services to build secure, highly available, and cost-efficient AI platforms.
- Lead implementations utilizing:
- AWS Bedrock
- Amazon SageMaker
- AWS Lambda
- ECS/EKS
- Amazon S3
- API Gateway
- Step Functions
- CloudWatch
- OpenSearch
- Architect cloud-native applications following AWS best practices.
- Optimize cloud infrastructure performance, scalability, and cost management.
DevOps, MLOps & Production Operations- Establish engineering best practices across:
- CI/CD Pipelines
- Infrastructure as Code
- Automated Testing
- Release Management
- Production Readiness
- Utilize:
- Docker
- Kubernetes
- Terraform
- GitHub Actions
- Drive application monitoring, troubleshooting, observability, and production support.
- Implement automated deployment and operational excellence frameworks.
Security, Governance & Responsible AI- Implement enterprise security controls including:
- Authentication
- Authorization
- Identity Management
- Data Privacy
- Governance Controls
- Support Responsible AI initiatives through monitoring, validation, and governance frameworks.
- Ensure compliance with industry regulations and enterprise security requirements.
- Implement guardrails, auditability, and observability controls for AI applications.
Technical Leadership & Mentorship- Conduct architecture reviews, design reviews, and code reviews.
- Mentor engineers and provide technical leadership across development teams.
- Establish software engineering standards, reusable frameworks, and development best practices.
- Collaborate with architects, engineers, product owners, data scientists, and cloud teams to deliver successful solutions.
- Drive innovation and continuous improvement initiatives across AI and software engineering programs.
Required Qualifications- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field required.
- Master's degree preferred.
- 6+ years of software engineering experience with significant hands-on experience in cloud-native application development.
- Strong understanding of AWS cloud architecture including:
- VPC
- IAM
- Networking
- Security
- Compute
- Storage
- Deep hands-on experience with:
- AWS Bedrock
- SageMaker
- Lambda
- ECS/EKS
- S3
- API Gateway
- Step Functions
- CloudWatch
- OpenSearch
- Strong understanding of AWS Bedrock AgentCore capabilities including:
- Runtime
- Gateway
- Identity
- Memory
- Observability
- Expertise in:
- Python
- JavaScript
- TypeScript
- React
- FastAPI
- Experience developing:
- RAG Pipelines
- LLM Applications
- Enterprise Search Solutions
- Knowledge Management Platforms
- Experience designing agent-based systems utilizing:
- LangGraph
- Strands Agents
- Comparable Agentic Frameworks
- Experience with:
- Docker
- Kubernetes
- Terraform
- GitHub Actions
- CI/CD Pipelines
- Strong understanding of:
- MLOps
- ModelOps
- Responsible AI
- AI Governance
- Model Monitoring
- AI Evaluation
- Experience working with:
- REST APIs
- Microservices
- Distributed Systems
- Event-Driven Architectures
- Knowledge of relational, NoSQL, search, and vector databases.
- Strong software architecture, performance optimization, testing, and production engineering skills.
Preferred Qualifications- Experience in financial services or other highly regulated industries.
- AWS certifications including:
- AWS Solutions Architect
- AWS Machine Learning Specialty
- AWS Certified Developer
- Experience implementing enterprise-wide AI platforms and governance frameworks.
- Familiarity with Langfuse or comparable AI observability platforms.
- Experience leading globally distributed engineering teams.
- Strong background in cloud cost optimization and operational excellence.
Technical ExpertiseCandidates should demonstrate expertise in:
- Generative AI
- Agentic AI
- AWS Bedrock
- AWS Bedrock AgentCore
- SageMaker
- LangGraph
- Strands Agents
- Retrieval-Augmented Generation (RAG)
- Enterprise Search
- Knowledge Management
- Python
- JavaScript
- TypeScript
- React
- FastAPI
- REST APIs
- Microservices
- Kubernetes
- Docker
- Terraform
- GitHub Actions
- MLOps
- ModelOps
- AI Governance
- Cloud Architecture
- Distributed Systems
Salary and Other CompensationThe annual salary for this position is anticipated to be between
$130,000 and $155,000 USD, depending on experience, qualifications, geographic location, skills, and other factors permitted by law.
In addition to base salary, this position may be eligible for:
- Annual performance-based bonus
- Merit-based compensation increases
- Employee referral bonuses, where applicable
The compensation information provided is accurate as of the date of this posting. Cognizant reserves the right to modify compensation information based on business needs and applicable laws.
BenefitsCognizant offers a comprehensive benefits package, including:
- Medical, Dental, and Vision Insurance
- Health Savings Account (HSA) and Flexible Spending Accounts (FSA)
- Life Insurance and AD&D Coverage
- Short-Term and Long-Term Disability Insurance
- Paid Time Off (PTO) and Company Holidays
- 401(k) Plan with Company Contributions (subject to eligibility)
- Employee Stock Purchase Plan (where available)
- Employee Assistance Program (EAP)
- Parental Leave and Family Care Benefits
- Tuition Reimbursement and Professional Development Programs
- Access to Learning, Certification, and Career Development Opportunities
Benefits are subject to eligibility requirements and plan terms.
