Experience: 8.00 + years

Salary: INR 6000000.00 / year (based on experience)

Expected Notice Period: 7 Days

Shift: (GMT+05:30) Asia/Kolkata (IST)

Chance Type: Office ()

Placement Type: Full Time Permanent position(Payroll and Compliance to be managed by: An AI platform for underwriting, claims, and insurance decision automation.)

(*Note: This is a requirement for one of Uplers client - An AI platform for underwriting, claims, and insurance decision automation.)

What do you need for this opportunity

Must have skills required:

BFSI, insurance, lending, Payments, Java, Springboot, Spring Boot, Kafka, Apache Kafka, Microservices, Domain Driven Design, DDD, System Design, HLD, LLD, Event Sourcing, Agentic AI, Python, PostgreSQL, AWS, CQRS, Immutable ledgers

An AI platform for underwriting, claims, and insurance decision automation. is Looking for:

THE ROLE

As Engineering Lead for the Backend Platform, you will spend the majority of your time writing production

code, designing distributed systems, and solving the hardest engineering problems on the platform.

Alongside that, you will provide technical direction and mentorship to 2–5 backend engineers - reviewing

their code with architectural depth, leading design sessions, and helping them grow.

Architecture & System Design

- Own architecture decisions for backend platform components end-to-end - from design through

deployment, monitoring, and iteration. You are not reviewing someone else's design you are making

the call.

- Design and implement event-driven insurance workflows - claims processing pipelines, underwriting

decision loops, policy lifecycle state machines - with write-path reliability as the non-negotiable

constraint.

- Define and enforce system decomposition principles: domain-driven boundaries, bounded contexts,

and coupling/cohesion trade-offs. Evaluate when not to over-engineer and make that call in code.

- Lead schema evolution strategy for long-lived insurance data: additive-only changes,

Liquibase/Flyway migration scripts, event versioning for immutable audit logs, and zero-downtime

rollout planning.

- Be the technical escalation point for complex distributed systems problems - Kafka pipeline failures,

distributed transaction consistency, performance degradation at scale, data integrity across service

boundaries.

Hands-On Engineering

- Write production-quality Java/Spring Boot code at a level that sets the bar for the engineers around

you - not prototype code, not proof-of-concept code.

- Implement and maintain Kafka-based event streaming pipelines: exactly-once semantics, dead letter

queues, consumer group management, partition strategy for insurance domain event volumes.

- Build for failure: implement the Transactional Outbox Pattern, Saga orchestration with compensating

transactions, Resilience4J circuit breakers (closed/open/half-open),



and idempotent consumers across

every service boundary.

- Integrate AI capabilities into the insurance platform backend - LLM-powered claim assessment,

RAG-based policy retrieval, agentic underwriting workflows - wherever the product roadmap demands

it.

- Own observability: design distributed tracing, structured logging, and Prometheus/Grafana metric

strategies so the team sees failures before customers do.

Technical Standards & Code Quality

- Conduct deep, architectural code reviews - not style reviews. Catch distributed systems anti-patterns,

consistency model violations, and write-path risks before they reach production.

- Define and enforce engineering standards: schema migration practices, API versioning discipline, test

coverage requirements for write-critical paths, and production readiness criteria.

- Write Architecture Decision Records (ADRs) for every significant technical call - what you chose, what

you rejected, and what the consequences are. Build the institutional technical memory.

CORE RESPONSIBILITIES - TEAM TECHNICAL LEADERSHIP (20–30%)

This is not a management role. You will not own hiring decisions, run performance review cycles, or manage

engineering budgets. The technical leadership responsibilities below are about multiplying the impact of the

engineers working alongside you - not about administration.

Technical Mentorship

- Provide technical direction to 2–5 backend engineers - help them understand the distributed systems

trade-offs behind every architectural decision, not just the decision itself.

- Pair on hard problems, review designs before implementation begins, and give feedback that teaches

rather than corrects.

- Identify skill gaps in the team proactively and address them through pairing, structured learning, or

technical deep-dives - not through escalation.

Design Reviews & Technical Governance

- Run design review sessions for significant backend changes - ensure domain boundaries are

respected, write-path reliability is considered, and the team is building something maintainable.

- Set the standard for what 'good looks like on this platform. Engineers should be able to look at your

code and your reviews to understand what the bar is.

- Contribute to technical hiring as a subject matter expert - evaluate candidates technical depth in

design discussions when needed, without owning the hiring process.

Non-Negotiable

- 8–12 years of software engineering experience with a strong and continuous Java/Spring Boot





production track record. You are still writing code every day in your current role.

- Currently in or coming from a technical lead or senior engineer role - not transitioning out of a

management role back into IC. The expectation is that you are at the peak of your technical output

right now.

- Apache Kafka production depth - consumer group management, partition strategy, exactly-once

semantics, DLQ design, and write-path reliability. Not configuration-level familiarity.

- Distributed systems ownership at implementation level - you can describe the schema of the outbox

table you built, the three states of the circuit breaker in your production system, and the specific failure

mode your Saga compensates for.

- Independent architectural reasoning - unprompted identification of failure modes, trade-off analysis

before being asked, and first-person design decisions with documented reasoning.

Insurance, payments, or lending domain experience - the regulatory compliance, audit trail

requirements, and data integrity constraints of BFSI systems are directly applicable to Anaira's

platform.

- Production AI integration - RAG pipelines, LLM orchestration, agentic workflows, or vector search in a

financial/insurance context. Anaira's product is AI-native the engineering team will be integrating

LLMs into critical insurance workflows.

- CQRS and Event Sourcing production experience - read model projections, command handlers,

immutable event logs with upcasters. Directly applicable to Anaira's audit and compliance

requirements.

- DDD (Domain-Driven Design) applied to a real system - not textbook. Bounded context decisions with

the trade-offs documented.

- Business process engine experience - Camunda, Flowable, or custom state machine implementations

for multi-step financial or insurance workflows.

- Open-source contributions, technical writing, conference talks, or public ADRs that demonstrate how

you think about engineering problems.

How to apply for this opportunity

- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!

About Uplers:

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(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).

So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

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