Software Senior Engineer
Pune, IN
About Avaya
Avaya is an enterprise software leader that helps the world’s largest organizations and government agencies forge unbreakable connections.
The Avaya Infinity™ platform unifies fragmented customer experiences, connecting the channels, insights, technologies, and workflows that together create enduring customer and employee relationships.
We believe success is built through strong connections – with each other, with our work, and with our mission. At Avaya, you'll find a community that values your contributions and supports your growth every step of the way.
Learn more at https://www.avaya.com
Job Information
Job Code: 00194006
Job Family: Research and Development
Job Function: Software Engineering
About The Opportunity
Engineer reusable agentic systems that transform platform development and day-two operations. Extend core platform practices—Terraform, Kubernetes, GitOps and cloud APIs—with agent tools, evaluations and safe execution. Scale this capability across the engineering team through shared architecture, workflows and hands-on enablement; do not treat agents solely as production-operation assistants. Work with startup-like urgency and hands-on ownership while preserving security, compliance and reliability.
What you will build
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Create a coherent agentic platform engineering approach: shared tool interfaces, reusable skills/workflows, coding conventions, evaluation harnesses, telemetry and adoption patterns.
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Develop agents and tools integrated with Terraform, Kubernetes, Argo CD/GitOps, cloud APIs, CI/CD, API gateways, Kafka, Redis, relational/document databases, observability and change-management systems.
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Accelerate platform development with AI-supported module/chart creation, code review, infrastructure plan interpretation, test generation, dependency analysis and safe pull-request workflows.
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Engineer day-two agents for health and drift detection, incident triage, correlated diagnostics, root-cause hypotheses, capacity analysis, upgrade readiness, runbook assistance and recovery verification.
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Build agentic development workflows for Kafka, Redis, relational/document database deployment and scaling, schema/configuration checks, upgrade planning, performance diagnosis, capacity assessments and secure API gateway changes.
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Use Prometheus, Grafana, Loki, Thanos, Grafana Alloy and OpenTelemetry as operational signal sources; engineer safe telemetry retrieval, correlation, retention-aware queries and verifiable diagnostic recommendations.
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Build controlled operational workflows progressing from read-only diagnosis to recommended actions, gated changes and policy-authorized execution where justified.
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Enforce scoped identity, least privilege, environment isolation, secrets protection, prompt/tool-injection resistance, input/output validation, human approvals, audit trails, timeouts, budgets, kill switches and rollback boundaries.
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Implement evaluation of agent correctness, false positives, tool behavior, failure handling, security conformance and outcome quality before production rollout.
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Embed compliance requirements into agent workflows: explainable decisions, traceable evidence, approved change paths, data minimization and continuous control validation for FedRAMP/PCI DSS/SOC 2 environments.
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Partner with security, SRE/CloudOps and platform teams to define where agents may observe, recommend or act; document accountable owners and escalation paths.
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Coach engineers through pairing, playbooks, examples and metrics so agentic development becomes a team capability rather than one specialist’s project.
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Lead adoption by embedding agentic development into real platform delivery in a fast-paced environment; pair with engineers, ship working patterns quickly and improve them through measurement and feedback.
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Measure adoption and value through cycle time, manual toil removed, diagnostic lead time, quality, safe automation rate and reliability; avoid rewarding unchecked autonomy.
About The Requirement
Required experience
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7+ years in software/platform engineering, DevOps or SRE with production Kubernetes, Terraform and GitOps depth.
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Strong Python or Go software engineering, API design, testing, integration and debugging skills.
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Hands-on building agentic workflows with LLM APIs, tool/function calling and orchestration; ability to explain working systems, evaluations and failure cases.
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Working understanding of Azure/GCP/AWS, identity, Kubernetes APIs, Argo CD, CI/CD, observability and change processes.
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Practical knowledge of Kafka, Redis, relational and document databases, API gateways and Kubernetes networking/security; ability to reason about scaling, deployment failures, observability and day-two recovery.
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Experience integrating with Prometheus/Grafana, Loki, Thanos, Alloy or comparable metrics, logging and telemetry backends to build reliable diagnostic workflows.
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Strong security judgment for privileged tools, least privilege, zero trust and data access in regulated enterprise environments.
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Ability to coach technical peers, standardize patterns and introduce new practices across teams without sacrificing operational reliability.
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Proven comfort with startup-like pace, ambiguous requirements, rapid iterations and shipping measurable engineering outcomes rather than demonstrations.
Preferred
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MCP and agent-tool protocols, retrieval where useful, event-driven systems, policy engines, sandboxed execution and human-in-the-loop workflows.
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Experience with FedRAMP, PCI DSS, SOC 2 technical evidence requirements and auditable automation.
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Cloud networking and platform services such as Istio, Keycloak, cert-manager, API gateways and DNS.
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Built or operated agents for diagnosis, remediation, deployment safety or infrastructure change at scale.
Success in the first 6–12 months
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Release a reusable, secured agent integration framework with evaluations, permission boundaries and traceability.
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Ship practical agentic workflows that improve Kafka, Redis, relational/document database/platform-service deployment, scaling, security validation and incident diagnosis using grounded observability signals.
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Deliver working agentic workflows that measurably improve development throughput and day-two diagnosis while preserving human accountability.
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Enable platform engineers to use shared tooling and repeatable practices; document uptake and quality metrics.
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Demonstrate a safe path from insights to approved actions, with explicit evidence of when automation should not act.
Leveling | Senior: owns production agent capabilities and integrations end to end. Principal: defines architecture, control boundaries, adoption strategy and engineering standards across teams.
Experience
Education
Preferred Certifications
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Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.
Avaya is an Equal Opportunity employer and a U.S. Federal Contractor. Our commitment to equality is a core value of Avaya. All qualified applicants and employees receive equal treatment without consideration for race, religion, sex, age, sexual orientation, gender identity, national origin, disability, status as a protected veteran or any other protected characteristic. In general, positions at Avaya require the ability to communicate and use office technology effectively. Physical requirements may vary by assigned work location. This job brief/description is subject to change. Nothing in this job description restricts Avaya right to alter the duties and responsibilities of this position at any time for any reason.