Software Engineer, Post-Trade Platform (Java/Angular)

Millennium Consulting; Bengaluru; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Millennium Consulting seeks a senior Java engineering lead to own end-to-end post-trade platform design and delivery. You will translate complex requirements into scalable technical designs, coach a small team, and drive architecture decisions for a cloud-native Kubernetes platform on AWS.

You will also champion AI-assisted automation and ensure robust testing, observability, and data integrity. Responsibilities include building event-driven microservices, integrating Kafka and REST APIs, and

Qualifications

• Hands-on experience building financial-services systems across the post-trade lifecycle.
• Strong understanding of post-trade data and controls.
• Lead-level Java expertise and modern architectural practices.

Responsibilities

• Own end-to-end design and delivery of a defined functional area within the post-trade platform.
• Translate requirements into technical designs, delivery plans, and scoped work.
• Lead, coach, and review a small development team; set quality standards.
• Design and build Java services with Spring Boot; contribute to Angular frontend.
• Make foundational architecture decisions for a cloud-native Kubernetes platform on AWS.
• Identify and deliver AI-enabled automation for operational processes with governance.
• Embed AI-assisted development practices and guardrails for AI-generated code.
• Collaborate with architecture, data, security, and global teams to deliver platform capabilities.

Skills

Java 17+

Spring Framework

Microservices

Event-driven architecture

Kafka

REST APIs

Angular

TypeScript

Kubernetes

AWS

CI/CD

SQL/Relational DBs

Tools

Spring Boot

Kafka

Angular

TypeScript

Kubernetes

AWS

Job description

What You'll Do

• Own the end-to-end design and delivery of a defined functional area within the post-trade platform, from requirements through production support.
• Translate post-trade requirements from Operations, Middle Office, and Finance stakeholders into clear technical designs, delivery plans, and well-scoped work.
• Lead, coach, and review the work of a small development team while setting standards for code quality, testing, observability, and documentation.
• Design and build event-driven Java services using Spring Boot, messaging, and REST APIs, and contribute to Angular front-end development for operations users.
• Make and document foundational architecture decisions for a greenfield, cloud-native platform running on Kubernetes in AWS.
• Identify and deliver AI-enabled automation for operational processes, including exception triage, break investigation, reconciliation matching, and processing unstructured confirmations, with appropriate controls and human oversight.
• Embed effective AI-assisted development practices and establish guardrails for reviewing, testing, and maintaining AI-generated code.
• Partner with architecture, data, infrastructure, security, control functions, and global colleagues to deliver reliable platform capabilities.

What You Bring

• Hands-on experience building financial-services systems across the post-trade lifecycle, including trade capture and enrichment, allocation, confirmation and affirmation, clearing, settlement, reconciliation, lifecycle events, and exception management.
• Strong understanding of the trade, position, cash, and reference data that support post-trade workflows, along with the associated operational controls.
• Lead-level Java expertise, including Java 17 or later, Spring, Spring Boot, microservice design, event-driven architectures, messaging platforms such as Kafka, RESTful APIs, relational databases, and SQL.
• Working experience with Angular and TypeScript, with the ability to build, review, and guide front-end development.
• Strong engineering discipline across automated testing, CI/CD, code review, observability, resilience, auditability, and data integrity.
• Practical, critical use of AI coding assistants and an understanding of LLM-based techniquesincluding retrieval-augmented generation, agents, document extraction, and classificationfor post-trade and Middle Office use cases.
• Awareness of AI-related accuracy, explainability, auditability, data-privacy, and human-review requirements.
• Proven experience leading a small team to deliver against agreed scope and timelines, with strong communication skills, sound judgment, and comfort operating in a greenfield environment.