Java / Spring boot Developer - AI Projects (Client Site)

About Vecton

Vecton is an AI-first technology partner dedicated exclusively to financial institutions. Unlike conventional IT consultancies, we go deep into finance. We design, build, and deploy AI-enabled solutions that span lending, trading, insurance, credit management, reconciliation, and wealth management.

What sets us apart is our ability to combine deep domain specialization with execution speed. We don't deliver pilots. We deliver production-ready systems that accelerate digital transformation while meeting the strictest compliance and regulatory standards.

We are guided by a clear set of values: speed with precision, domain depth in financial institutions, trust and compliance, partnerships over vendors, an AI-first mindset, and continuous improvement.

Our motto: Transform Businesses with Technology and AI.

About the Role

As a Java Developer, you will be Vecton's engineering presence embedded within the client's environment. You will own the build and delivery of AI-enabled systems inside a regulated financial institution.

Our central team designs and architects AI solutions for complex financial use cases. Your job is to turn those designs into production-grade Java and Python services that run reliably inside the client's stack. They will be integrated with the client's core systems, released through the client's pipelines, and compliant with the client's security controls.

This is a forward-deployed, high-ownership role. You will report to Vecton's central engineering team, with a dotted-line accountability to the client's technical leadership.

What You'll Do

• Build and ship production-grade Java / Spring Boot services that expose, orchestrate, and integrate AI capabilities, including LLM calls and multi-agent workflows.
• Build and ship Python-based AI services (FastAPI, agent/RAG pipelines) alongside Java services, and define clean contracts between the two.
• Own delivery from development and code review through build, release, and post-deployment support.
• Work within the client's CI/CD pipelines and release governance, and handle configuration and secrets as per their standards.
• Add basic logging and metrics to your services, and drive RCA and permanent fixes for production issues.
• Identify manual, repetitive work in the client's engineering and business processes and automate it.
• Build integrations between AI systems and existing client applications, databases, message queues, and APIs, including core banking / LOS / LMS / CRM systems where applicable.
• Provide technical inputs to solution design and effort estimation for new scope within the account.
• Run technical walkthroughs and PoC demos that build client confidence.
• Actively use AI-assisted development tools (Cursor, Copilot or equivalent) to accelerate delivery and improve code quality.

What We're Looking For

• 3-6 years of hands-on software development experience, with Java as the primary language.
• Strong command of Java 11/17+, Spring Boot, Spring Data, dependency injection, and multithreading/concurrency fundamentals.
• Proven experience designing and building RESTful APIs and microservices. You should be comfortable with JSON, API contracts, versioning, and error handling.
• Solid SQL and RDBMS experience (Oracle / PostgreSQL / MySQL), and familiarity with message queues (Kafka, RabbitMQ, or equivalent).
• Build and dependency tooling (Maven or Gradle), plus unit and integration testing (JUnit, Mockito).
• Experience with containerization and orchestration (Docker, Kubernetes) and/or traditional app server deployments (Tomcat, WebLogic).
• Working knowledge of large language models, prompt engineering, RAG, and agentic AI concepts.
• Python (working proficiency): building and deploying AI services (FastAPI/Flask), LLM API integration, RAG, vector stores, and agent frameworks (LangChain/LangGraph or similar).
• Experience integrating LLM APIs into services, via Python AI services or Java-native frameworks (Spring AI, LangChain4j).
• Genuine curiosity about the rapidly evolving AI tooling landscape and the initiative to keep pace with it.

Good to Have

• Golang: experience building high-throughput or concurrent services, gRPC.
• Exposure to BFSI systems (LOS/LMS/core banking), RBI/DPDPA-aware design, and audit/data-masking patterns.
• Observability tooling (Grafana/Prometheus, ELK, OpenTelemetry), Jenkins/GitLab CI.