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: 00194005 Job Family: Research and Development Job Function: Software Engineering
Position Overview
We are seeking a high-performing, hands-on Principal Engineer to lead the development of reliable integrations and next-generation AI platform capabilities for Avaya Infinity™. In this role, you will bridge the gap between distributed systems engineering and machine learning operations (MLOps) to build a robust foundation for intelligent, agent-assisted workflows.
Agentic development is at the absolute core of our engineering philosophy. You will not just write code; you will act as a systems architect and director, guiding AI coding agents to implement solutions while you retain ultimate ownership of system design, security, reliability, and production behavior.
Ownership and Delivery
- Proactive Problem Solving: Actively identify architectural and operational gaps, propose structured solutions, and assume end-to-end ownership to drive initiatives from concept to successful completion.
- Transparent Communication: Articulate technical trade-offs with clarity, surface project blockers early to prevent timeline slips, and actively share knowledge to elevate the technical capabilities of the peer team.
- Post-Release Accountability: Maintain steadfast accountability for code in production by investigating system failures, synthesizing user feedback, and continuously iterating to improve performance and reliability outcomes.
Responsibilities
- Design and implement services connecting enterprise applications, data platforms, models, and tools through APIs and asynchronous messaging.
- Automate model and application lifecycle management, including versioning, reproducibility, evaluated promotion, controlled rollout, and rollback.
- Implement authentication, permissions, isolation, and recovery across system boundaries while evolving interfaces without breaking consumers.
- Work with AI engineers on release quality and operate inference and agent services, improving availability, latency, and cost.
- Lead agentic delivery across services, integrations, and release automation, sharing reusable practices.
Required Experience
- Hands-on production development in Go (Golang) or Rust and working Python proficiency, with personal ownership of system design and implementation.
- Substantial systems integration experience. Ability to explain API contracts, compatibility, concurrency, asynchronous behavior, retries, idempotency, authentication, and failures across distributed services.
- Production MLOps experience with reproducible training or model packaging, artifact tracking, deployment, monitoring, and rollback. Experience supporting batch or online inference and ML or AI workloads on Databricks.
- Production delivery on GCP or Azure using automated tests, CI/CD, identity controls, and observability. Personal responsibility for troubleshooting and improving services after release.
Required Agentic Development Experience
- Demonstrated delivery of a substantial feature, service, integration, or engineering tool from proof of concept into production using coding agents such as Codex, Cursor, or equivalents.
- Decompose work, provide repository context and constraints, coordinate parallel tasks across files and components, maintain reusable agent instructions, and critically review and integrate generated changes.
- Independently understand, maintain, and debug the code. Explain agent mistakes caught, tests with independently established expectations, security and performance checks, CI/CD, hardening, rollout, rollback, and verified production outcomes.
- Learn unfamiliar systems with AI and apply that understanding after release. Tool familiarity, autocomplete, or prototype-only work does not establish this experience.
Preferred Experience
- Advanced LLM Orchestration: Hands-on experience designing and operating LLM provider integrations, multi-model routing systems, runtime usage and cost controls, semantic drift monitoring, and evaluation-driven release pipelines.
- Robust Runtime Architectures: Deep expertise building agent runtimes, orchestrating durable workflow engines, and delivering highly concurrent production systems using both Go and Rust across multi-cloud environments (GCP and Azure).
Education
Bachelor degree or equivalent experience
Pay Transparency
The pay range for this opportunity is from $179,127 to $234,100 + benefits. This range represents the anticipated low and high end of the salary plus bonus for this position. Actual total compensation will vary and is based on factors such as a candidate’s qualifications, skills, and competencies.
Sponsorship and Equal Opportunity
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.
