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Genesys seeks a Principal Engineer to design and evolve backend platforms powering Agentic AI workloads. You’ll own the technical strategy for core services, data and runtime foundations, and lead multiple teams to deliver secure, low-latency systems at global scale.
The role offers hybrid work from Galway or remote within Ireland, with in-person collaboration 2–3 times monthly. You’ll mentor staff engineers and drive security, reliability and governance in enterprise AI systems.
Be the one building AI-powered experiences where they matter most. At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships. Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day. The Genesys Digital & AI group builds the innovations that power customer experiences for 8,000+ organisations worldwide. As a Principal Engineer you’ll design and evolve the backend platforms that make our Agentic AI products possible. You’ll own the technical strategy for core services, data, and runtime foundations; partner closely with Agentic AI specialists; and lead multiple teams to deliver secure, reliable, low‑latency systems at global scale.
Location: This role is open to candidates who wish to work in a hybrid capacity from our Galway office or remotely within Ireland. Please note that the team collaborates regularly in our Galway office, and remote employees will be expected to attend in person a minimum of 2–3 times per month.
Own the multi‑year backend strategy. Define north‑star architectures for APIs, data flows, events/streams, storage, consistency, and multi‑tenant isolation that underpin Agentic AI workloads.
Standardise service templates, libraries, REST/event patterns, schema versioning, automated testing, and documentation that accelerates multiple teams.
Design for scale, reliability, and cost. Drive SLOs/SLA design, capacity planning, graceful degradation, performance engineering, and cost/stewardship for traffic and LLM‑adjacent workloads.
Comply with Data platform & governance rules. Shape ingestion, transformation and cataloguing; ensure lineage, retention, residency and privacy‑by‑design; make data easy to use and hard to misuse.
Ensure operational excellence. Lead CI/CD, IaC, progressive delivery, runtime hardening, observability and on‑call practices; turn incidents into systemic fixes.
Put security first. Champion threat modelling, least‑privilege IAM, secrets management, API authz/authn, and compliance controls.
Partner with AI specialists. Co‑design interfaces, contracts and back‑pressure strategies for agents, RAG, tool calling and eval loops; hide complexity behind stable, well‑documented APIs.
Lead major programmes. Cross‑team migrations, region expansion, service architecture, eventing upgrades, tech debt reduction and deprecations.
Influence through writing and reviews. Review PR’s, give constructive feedback, create/update high level architecture docs; communicate decision trade‑offs clearly to engineers, PMs and execs.
Multiply talent. Coach Staff Engineers and tech leads; raise the bar on design, code quality and operational maturity across multiple teams.
Bachelor’s or Master’s in Computer Science or related disciplines.
8+ years building and operating backend / platform software, with evidence of technical leadership and impact across teams.
Deep skill in Java and/or Python, and strong fundamentals in algorithms, data structures and distributed‑systems design.
Proven experience with event‑driven and service‑oriented architectures (e.g., Kafka/Kinesis/SQS; REST APIs), schema evolution, idempotency, and backwards‑compatible APIs.
Expertise running on AWS at scale (IAM, networking, DynamoDB/RDS, S3, ECS/serverless, CloudWatch/OpenTelemetry) and modern DevOps/SRE (CI/CD, IaC, automated testing, runbooks).
Track record of setting standards and unblocking/aligning multiple teams via influence; excellent communicator who maps technical choices to business outcomes.
Evidence of performance and cost optimisation in latency‑sensitive, high‑throughput systems (profiling, caching, load shedding, rate limiting, async pipelines).
Comfortable partnering with AI/ML teams and supporting LLM‑adjacent systems (feature stores, vector stores, evaluation harnesses, safety/guardrails) even if you’re not the model expert.
Pragmatism, bias to action, and a growth mindset.
Demonstrates awareness of AI-enabled systems and associated risks and responsibilities, applying appropriate technical practices to support secure, reliable, and responsible AI system behaviour.
Analytics and data science frameworks/technologies, e.g. Apache Spark, Pandas.
Machine learning concepts and frameworks.
LLM systems concepts (tooling, retrieval, evals) and cost/latency trade‑offs.
Security, privacy and governance of enterprise software.
Genesys® empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud™ is the AI-Powered Experience Orchestration platform that connects people, systems, data and AI across the enterprise. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces.
If you require a reasonable accommodation to complete any part of the application process, or are limited in your ability to access or use this online application and need an alternative method for applying, you or someone you know may contact us at reasonable.accommodations@genesys.com. You can expect a response within 24–48 hours.
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