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Engineering Manager - Agentic SDLC

Arintra

Bangalore, Karnataka, IndiaOtherNo compensation foundPosted 2w agoVerified open 5 days ago

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At a glance

Compensation
No compensation found
Location
Bangalore, Karnataka, India
Schedule
Other
Work Authorization
Not specified

Job overview

Arintra seeks an Engineering Manager to lead agentic SDLC adoption, overseeing Java and microservices teams, driving process change, and ensuring production reliability. The role demands strong technical critique, stakeholder collaboration, and hands‑on leadership in tooling, estimation, and QA practices within a fast‑moving engineering organization.

Skills & qualifications

RequiredNice to have

Skills

Quality AssuranceSDLCSpring BootPerformance ManagementJavaFailure AnalysisSOA/MicroservicesMicroservicesClaude CodeCursorCodexDevinCopilot Agent ModeDesignImplementationReviewTestingProduction DebuggingEstimationQA PracticesFailure Modes AnalysisStakeholder ManagementNew RelicDatadogPrometheusGrafanaGCPAWSPostgreSQLElasticsearchNeo4jFHIRHL7Medical Coding

Qualifications

9+ Years Software Engineering Experience3+ Years Engineering Management ExperienceAgentic SDLC Adoption Experience

Full job description

Requirements:

  • 9+ years in software engineering with 3+ years managing engineers directly, including hiring and performance management.
  • Strong technical grounding in Java, Spring Boot, and microservices enough to review a design doc critically, push back on an architecture, and read a PR. You will not be writing most of the code, but you cannot be a spectator.
  • Hands-on experience leading a team through agentic SDLC adoption in the last 12 months with tools such as Claude Code, Cursor, Codex, Devin, Copilot agent mode, or equivalent, applied across at least three of: design, implementation, review, testing, and production debugging.
  • Demonstrated ability to change process, not just tooling: concrete examples of estimation, review, or QA practices you rewrote because agentic workflows made the old ones wrong.
  • A clear point of view on the failure modes: review fatigue, plausible-but-wrong tests, context loss on large codebases, skill atrophy in junior engineers, and inflated velocity that hides quality debt.
  • Plus what you did about each.
  • Track record of delivering in production with real accountability for reliability and on-call.
  • Strong stakeholder management across product, domain experts, and leadership.

Nice to have:

  • Scaled a team's output measurably (with the metrics to back it) after agentic adoption.
  • Built or sponsored internal agent tooling: custom agents, MCP integrations to Jira/BigQuery/observability, repo-level instruction files.
  • Experience rethinking career ladders or interview loops for an agent-assisted engineering org.
  • LLM evaluation, regression harnesses, or accuracy pipelines.
  • Observability practice ownership (New Relic, Datadog, Prometheus/Grafana) and agent-assisted incident triage.
  • Healthcare, FHIR/HL7 or medical coding domain exposure.
  • GCP or AWS; PostgreSQL, Elasticsearch, Neo4j.

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