Java Architect – Agentic AI
& Legacy Modernization
Location: Merrill Lynch, NJ – Onsite
Job Type: C2C / Contract
Job
Summary
We are seeking a Senior Technology Lead –
Agentic AI & Legacy Modernization to lead the design and delivery of
AI-driven modernization initiatives. This is a highly hands-on technical
leadership role focused on combining Agentic AI, legacy system
modernization, and cloud-native engineering.
The ideal candidate will have strong experience
building custom AI agent pipelines and multi-agent systems, while also
possessing deep expertise in legacy technologies such as COBOL, CICS, IMS,
DB2, JCL, IBM MQ, and modern technologies including Java 21, Spring
Boot, Angular, MongoDB, Kubernetes, and cloud platforms.
The candidate will lead cross-functional
engineering teams, own solution architecture, perform code reviews, build AI
agents, and drive modernization initiatives from legacy analysis through
migration and production deployment.
Key
Responsibilities
Agentic AI & AI-Driven Modernization
- Design
and deploy custom AI agent pipelines to analyze and
reverse-engineer legacy applications.
- Build
multi-agent workflows for code analysis, business-rule extraction, data
mapping, testing, and modernization.
- Develop
agentic solutions using platforms/frameworks such as Claude Code CLI,
Cursor, Gemini CLI, LangChain, LangGraph, AutoGen, and CrewAI.
- Implement
tool/function calling, RAG, agent memory, human-in-the-loop workflows, and
validation mechanisms.
- Develop
prompt engineering strategies for code extraction, generation, validation,
and refinement.
- Evaluate
agent output quality and implement validation frameworks to minimize
hallucinations and ensure accuracy.
- Work
with LLM APIs such as Anthropic Claude, Google Gemini, OpenAI GPT,
or equivalent platforms.
Legacy Modernization
- Analyze
and reverse-engineer legacy COBOL, CICS, IMS, DB2, JCL, Assembler, IBM
MQ, and related systems.
- Extract
business rules, dependencies, data flows, domain models, and application
relationships from legacy estates.
- Design
modernization strategies including Strangler Fig, Anti-Corruption
Layer, event interception, dual-write, and dual-read patterns.
- Drive
migration from legacy platforms toward modern cloud-native architectures.
- Validate
migrated application behavior against legacy systems and identify
functional discrepancies.
Modern Cloud-Native Engineering
- Design
and develop modern applications using Java 21 and Spring Boot 3.x.
- Build
RESTful APIs and microservices following scalable cloud-native
architecture patterns.
- Develop
and maintain MongoDB schemas, aggregation pipelines, and indexing
strategies.
- Work with
Angular/TypeScript, RxJS, and modern UI architectures.
- Design OpenAPI
3.1 contract-first APIs.
- Integrate
and modernize IBM MQ toward Kafka, Azure Service Bus, or equivalent
messaging platforms.
- Implement
distributed systems patterns including circuit breakers, retry/backoff,
service mesh, distributed tracing, and structured logging.
Cloud & DevOps
- Design
and deploy cloud-native solutions using AWS, Azure, or GCP.
- Work
with Docker and Kubernetes for containerized application
deployment.
- Develop
and govern Infrastructure-as-Code using Terraform and/or Helm.
- Design
CI/CD pipelines using GitHub Actions, Jenkins, or Azure DevOps.
- Implement
automated quality gates, security scanning, test coverage, and container
image scanning.
- Ensure
AI-generated code and infrastructure artifacts pass appropriate
engineering and security review processes.
Technical Leadership
- Lead
cross-functional teams covering backend, frontend, data migration, and
AI/agent engineering.
- Own
end-to-end solution design and technical architecture for modernization
workstreams.
- Prepare
LLDs, sequence diagrams, data-model mappings, migration roadmaps, and API
designs.
- Conduct
architecture and code reviews across both manually written and
AI-generated code.
- Establish
engineering standards for agent-assisted development.
- Mentor
engineers on Agentic AI, prompt engineering, legacy modernization, and
cloud-native development.
- Work
closely with architects, legacy SMEs, domain engineers, cloud teams, and
business stakeholders.
Delivery & Stakeholder Management
- Own
technical delivery commitments and sprint-level execution.
- Break
modernization initiatives into measurable engineering deliverables.
- Track
modernization progress, migration coverage, and agent pipeline quality.
- Identify
technical risks including AI hallucination, data consistency, performance
gaps, and migration issues.
- Communicate
architecture decisions, technical risks, blockers, and mitigation
strategies to stakeholders.
Required
Skills & Experience
Agentic AI – Must Have
- Hands-on
experience building multi-agent AI systems.
- Experience
with one or more of:
- Claude
Code CLI
- Cursor
- Gemini
CLI
- LangChain
/ LangGraph
- AutoGen
- CrewAI
- Equivalent
Agentic AI frameworks
- Strong
understanding of agent orchestration patterns such as:
- Sequential
chains
- Parallel
workflows
- Supervisor/worker
models
- Reflection/self-critique
loops
- Experience
with LLM tool/function calling.
- Experience
with RAG and agent memory strategies.
- Strong
prompt engineering experience.
- Experience
evaluating and validating AI-generated outputs.
- Knowledge
of LLM APIs such as Claude, Gemini, OpenAI GPT, or equivalent.
Legacy Modernization – Must Have
- 15+ years of software engineering
experience with
strong technical leadership background.
- Strong
ability to understand and analyze:
- COBOL
- CICS
- IMS
- DB2
- JCL
- IBM MQ
- Experience
with enterprise legacy modernization programs.
- Strong
understanding of modernization patterns including Strangler Fig,
Anti-Corruption Layer, event interception, dual-write, and dual-read.
Modern Development – Must Have
- Deep
expertise in Java 21.
- Strong Spring
Boot 3.x experience.
- Microservices
and REST API development.
- MongoDB and document data modeling.
- Angular / TypeScript.
- OpenAPI
3.1.
- JUnit 5
/ Mockito.
- Experience
with IBM MQ and modern messaging technologies such as Kafka or Azure
Service Bus.
Cloud & Infrastructure
- Production
experience with AWS, Azure, or GCP.
- Docker
and Kubernetes.
- Terraform
and/or Helm.
- Cloud-native
architecture and distributed systems.
- OpenTelemetry,
structured logging, monitoring, and observability.
CI/CD & DevSecOps
- GitHub
Actions, Jenkins, or Azure DevOps.
- Automated
testing and quality gates.
- SonarQube
and OWASP dependency scanning.
- Container
security/image scanning.
- Secure
CI/CD and deployment practices.
Preferred
Qualifications
- Experience
with enterprise-scale AI-driven application modernization.
- Experience
in financial services, banking, insurance, or other highly regulated
environments.
- Experience
designing AI agents specifically for legacy code analysis and migration.
- Experience
with Spring Expression Language (SpEL), Drools, or similar rules engines.
- Strong
experience with event-driven architecture.
- Excellent
communication, stakeholder management, and technical leadership skills.
Education
- Bachelor's
degree in Computer Science, Engineering, Information Technology, or a
related technical discipline preferred.
Feel free to let me know
if you have any questions.