Software Development Engineer, II

Ovii's Interpretation of the Role

The Software Development Engineer II will own core components of kAIgentic’s AI workflow orchestration platform, building durable, observable backend services for enterprise customers. The role blends deep Go/Python engineering with distributed systems, LLM orchestration, and production‑grade observability.

Role Snapshot

• Own durable AI workflow execution
• Design observability pipelines
• Develop gRPC services & service‑mesh integrations
• Build LangGraph‑based model coordination
• Collaborate on AI‑native development practices

Must-Have Requirements

• Go
• Python
• Temporal or Cadence
• gRPC
• Service‑mesh architecture
• Distributed systems fundamentals
• Observability (Langfuse, Arize Phoenix)
• LLM orchestration & self‑correction
• LangGraph coordination
• backend and infrastructure systems for enterprise AI workloads
• durable execution engines (Temporal/Cadence)
• distributed systems fundamentals

Nice-to-Have Signals

• AI‑native velocity as a default mode of working
• AI‑native development practices

Work Setup

• Location: Bengaluru, India
• Work mode: HYBRID
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Education requirement
• Certifications
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Design and implement durable workflow execution using Temporal or Cadence, ensuring stateful long‑running processes survive failures.
• Create LangGraph‑driven coordination across multiple LLMs and tools for seamless multi‑model orchestration.
• Build self‑correction loops that validate LLM outputs and trigger automated re‑prompting on schema mismatches.
• Develop end‑to‑end observability pipelines with Langfuse and Arize Phoenix for tracing and metrics.
• Improve interrupt‑and‑resume patterns for human‑in‑the‑loop workflows, enhancing reliability under production load.
• Collaborate with cross‑functional engineers to embed AI‑native development practices and raise code‑review rigor.
• Implement gRPC services and integrate them into a service‑mesh for scalable state management across distributed environments.

Good Fit If You Have

• Experience delivering backend and infrastructure systems for enterprise AI workloads.
• Comfort translating ambiguous requirements into reliable production solutions.
• Strong customer empathy and ability to communicate effectively with stakeholders.