Staff Software Engineer

Role:Staff Software Engineer(8-12 Years)

Location:Bangalore

Summary:

Defines and drives the technical direction of Tekion’s Orbit platform . Operates at the

intersection of deep hands-on engineering and cross-team architectural leadership. Brings 7–10

years of software engineering experience anchored in Java, with proven expertise in agentic

orchestration, LLM pipeline design, and production-grade AI systems. Serves as a technical

authority, influencing platform strategy, raising the engineering bar, and enabling multiple teams

to move faster and build better.

Duties & Responsibilities

• Own and drive the end-to-end technical architecture of AI agent systems, including multiagent orchestration, LLM integration, vector and graph data layers, and durable workflow

execution.

• Define platform-level patterns and reusable frameworks for agentic development using

LangChain, LangGraph, and LangFlow — enabling other teams to build reliably on top of

shared foundations.

• Lead the design and adoption of Qdrant-based semantic search and retrieval pipelines, and

establish standards for knowledge graph modelling using Neo4j across platform teams.

• Architect fault-tolerant, long-running agent workflows using Temporal, defining reliability

and retry patterns that serve as the organisational standard.

• Establish and own the observability strategy for AI workloads — covering LLM call tracing,

token cost attribution, latency SLOs, and agent decision transparency.

• Partner with engineering managers, product managers, and architects to translate business

goals into multi-quarter technical roadmaps.

• Identify and resolve systemic technical risks, cross-team dependencies, and architectural gaps

before they become production incidents.

• Conduct architecture reviews, set coding and design standards, and drive consistency across

teams building on the AI platform.

• Mentor Senior and mid-level engineers; invest in technical growth across the organisation

through design reviews, documentation, and knowledge sharing.

• Represent engineering in cross-functional forums; communicate technical strategy and tradeoffs clearly to CTO, VP, and product leadership.

• Champion quality at a platform level — define test strategy, enforce contract testing between

services, and drive observability-driven development practices.

Qualifications Required:

• 8–12 years of professional software engineering experience with Java as the primary

language.

• Demonstrated experience architecting and operating LLM-based agentic systems in

production using LangChain, LangGraph, or LangFlow.

• Deep expertise with Qdrant or equivalent vector databases for large-scale semantic search

and retrieval-augmented generation (RAG) pipelines.

• Strong experience with Neo4j or graph databases for complex domain modelling, knowledge

graphs, and relationship-driven query patterns.

• Proven experience with Temporal or a comparable durable execution platform (Conductor,

Cadence) for orchestrating fault-tolerant, long-running workflows at scale.

• Expert-level understanding of multi-agent orchestration: planning, tool use, ReAct and

reflection patterns, memory architectures, and agent evaluation.

• Strong observability engineering background: OpenTelemetry, distributed tracing, metrics

pipelines, LLM-specific telemetry, and SLO/SLA management.

• Track record of defining and enforcing engineering quality standards — test architecture,

coverage strategy, code review culture, and zero-defect production mindset.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.

• Excellent written and verbal communication; able to influence without authority across

engineering, product, and executive stakeholders.

Preferred:

• Experience building internal developer platforms or shared engineering frameworks adopted

by multiple product teams.

• Familiarity with LLM cost governance — token budgeting, model tiering, context window

optimisation, and inference cost attribution at scale.

• Exposure to automotive retail technology, dealer management systems, or enterprise SaaS

platforms with high regulatory or reliability requirements.

• Contributions to open-source AI or agent orchestration tooling, or published technical writing

in the agentic systems space.

• Experience with security hardening for LLM systems: prompt injection defences, output

validation, data residency, and PI…