Tekion Corp
Website:
tekion.com
Company:
https://www.linkedin.com/company/tekion
Industries: Software Development
Job details:
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 PII handling in AI pipelines
Click on Apply to know more.