Senior AI/ML Engineer - Remote
Hartford, Hartford County, Connecticut, 06112, USA
Listed on 2026-05-11
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IT/Tech
Cloud Computing, Systems Engineer
Join the Contact Center Voice modernization journey modernizing a mission critical voice channel that supports 300M+ calls annually. You will help migrate legacy contact center capabilities off on‑prem platforms and into multi‑cloud (AWS + Google) solutions, building scalable voice experiences, accelerating feature migrations and strengthening reliability and governance for AI‑enabled customer interactions. If you enjoy solving complex, high‑impact engineering problems with modern cloud stacks (CI/CD, microservices, automation) and shaping responsible AI practices in production, this role is for you.
You’ll enjoy the flexibility to work remotely from anywhere within the U.S. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Primary Responsibilities- Lead cloud migrations of traditional voice contact center capabilities from legacy platforms to Google Dialogflow and Amazon (Connect/Lex) solutions, partnering across engineering, platform, and business teams.
- Own solution design and delivery for cloud‑based contact center components (voice bot/IVR workflows, orchestration/integrations, deployment patterns), ensuring production readiness end‑to‑end.
- Rapidly learn and apply new ecosystem patterns to accelerate bot + IVR modernization—adapting to evolving requirements and scaling reusable approaches across work streams.
- Drive cross‑functional execution: collaborate with Platform/Steering/CCaaS teams, SRE/Operations, QA/Perf, and business stakeholders to align dependencies and deliver outcomes.
- Establish and evolve Dev Ops best practices for build/release automation, observability, and environment hygiene using modern CI/CD and source control practices (e.g., Git Hub‑based workflows).
- Build and enhance automation tooling, including the Bot Certification Tool, to streamline governance, compliance workflows, and developer productivity across contact center engineering.
- Engineer for reliability, scalability, and security: design with least‑privilege, resilient architectures, performance considerations, and solid operational monitoring for production voice experiences.
- Partner with SI vendors and internal teams to define deliverables, execute migration plans, and ensure value realization through measurable outcomes.
- Operationalize “Responsible AI” by supporting a Machine Learning Review Board approval process—embedding governance, traceability, and risk controls into AI/LLM‑enabled solutions.
- 3+ years of experience building and operating cloud‑native solutions with Dev Ops practices (CI/CD, automated testing, release management, and monitoring) in production environments.
- 3+ years of experience delivering digital contact center/channel solutions at scale (Voice Bot, Chat Bot or related orchestration/integrations) with production support accountability.
- 3+ years of experience implementing AI/ML capabilities, including practical exposure to LLM‑enabled features (prompting/guardrails, evaluation, monitoring, or governance) in enterprise settings.
- 3+ years of hands‑on experience with AWS and/or GCP, including cloud architecture fundamentals.
- 3+ years of experience building modern applications and services using React and Python/JavaScript/NodeJS, including microservices or micro‑app patterns.
- Demonstrated ability to quantify engineering and operational tradeoffs (cost, reliability, performance, and maintainability) and communicate those decisions to stakeholders.
- Proven track record of innovation/optimization in established bot or IVR landscapes—e.g., automation accelerators, reusable frameworks, or delivery improvements that reduce cycle time or risk.
- Proven solid cross‑functional collaboration skills, including experience working with platform teams, product/business partners and SI vendors to deliver outcomes.
- Direct experience with Amazon Lex / Amazon Connect and/or Google Dialogflow implementations for enterprise voice workflows.
- Experience building internal developer platforms/tools (e.g., governance workflows, certification pipelines, UI‑driven tooling).
- Experience supporting large‑scale…
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