Role: Software Engineer, Quality & Observability

Full time | Engineering | Remote / Hybrid

Notice Period: Immediate - 15days

Experience: 7+yrs Our company

Ignite the future of enterprise AI We believe that people thrive when empowered with better information.

Autonomous Knowledge

Platform activates enterprise intelligence by unifying data, knowledge, and business context to achieve tangible outcomes. With organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. delivers real business value with AI.

We have built the most comprehensive cloud analytics and data platform for AI, designed to deliver harmonized data, Trusted AI, and accelerated innovation. This enables our customers, and their customers, to make smarter, more confident decisions. Our platform is trusted by the world's leading enterprises across every major industry to enhance business performance, elevate customer experiences, and unify data across the organization.

We are pushing the boundaries of artificial intelligence, especially in autonomous and agentic systems. Our intelligent technologies go far beyond automation. They observe, reason, adapt, and drive complex decision-making at enterprise scale.

The opportunity

What you'll do: quality and signal at enterprise scale

As a Software Engineer on our Quality & Observability team, you will own the testing and telemetry that let us ship a major platform release with confidence. Our systems are distributed and event-driven, built on containerized services with eventual consistency at their core. You will design the functional test coverage and the observability instrumentation that prove those systems behave correctly and stay measurable in production.

This is hands-on engineering across a heterogeneous, multi-service estate,

guided by architecture and standards rather than by any single codebase. In this role, you will:

Design and build functional and contract test assets for cloud-native services, asserting on real system state and side effects,



not just on HTTP response codes

Instrument services end to end with OpenTelemetry, producing traces and metrics that export cleanly and remain usable for real operational monitoring

Derive test cases and telemetry points directly from architecture documentation, ensuring every documented invariant has a test and every named span or metric is actually observed

Build test patterns for distributed, asynchronous systems that respect eventual consistency, readiness gating, and lifecycle signals rather than assuming synchronous request and response

Design representative test data and fixtures for a complex domain, including patterns for validating probabilistic and AI-generated outputs against thresholds and golden datasets

Work independently across many repositories, following documented conventions with minimal hand-holding and contributing improvements back to shared tooling and CI workflows

Collaborate with product owners, architects, and cross-functional teams to deliver release-critical quality and telemetry work on schedule What makes you a qualified candidate

Skills in action

We are seeking engineers with a strong foundation in DevOps practices, containerization, and the realities of testing distributed systems. You bring:

Strong proficiency in Python and a modern test framework such as pytest, comfortable writing tests to a repository's established conventions

Hands-on experience with Docker and Docker Compose, able to read and extend container definitions to compose real service dependencies locally rather than mocking them

Solid literacy in distributed and event-driven systems, including message-driven architectures, eventual consistency,



and asynchronous processing patterns

Experience with API and contract testing against HTTP services, including modern Python frameworks such as FastAPI

Familiarity with validating side effects across data stores such as relational databases, search indexes, and graph or NoSQL systems after a change or mutation

Experience testing message-driven flows: producing test events, asserting consumer-side effects, and reasoning about partitioning and ordering semantics

Comfort designing assertions for probabilistic or model-generated output using threshold-based and golden-dataset patterns rather than exact matching

Disciplined Git and GitHub workflow habits, including branch strategy and pull-request review gates The ability to work from an architecture document, deriving test cases and instrumentation points from documented behavior and invariants Observability and instrumentation

Telemetry expertise

This role has a strong observability focus. Ideal candidates bring:

Hands-on experience with the OpenTelemetry SDK, instrumenting services for traces and metrics with OTLP export

Experience instrumenting HTTP services and agent or worker components, using auto instrumentation libraries where available

Understanding of trace-context propagation across service and asynchronous message boundaries, not just HTTP header propagation

Familiarity with observability backends such as Grafana, Loki, Tempo, and Mimir, useful for verifying that instrumentation produces genuinely usable signal A config-driven approach to instrumentation that respects environment-based configuration and avoids hardcoded endpoints Bonus points

Nice to have

Experience with GitHub Actions or comparable CI pipelines, including shared or reusable workflows

Exposure to OpenTelemetry instrumentation in Rust, using the tracing ecosystem

Prior work with knowledge graphs, data catalogs, or metadata-management platforms

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience

📌 Quality& Observability Engineer IIII (India)
🏢 SysTechCorp
📍 India