Build and operate backend services, asynchronous workflows, and asset pipelines supporting conversational AI experiences. Manage versioned AI configurations, prompts, knowledge artifacts, and media assets; integrate shared services and external APIs; implement security, observability, retries, testing, release, and rollback processes. Evaluate compatibility, privacy, licensing, reliability, storage, processing time, and vendor costs while collaborating with engineering teams and digital-human specialists.
This is a remote position.
****If not located in LATAM, PLEASE DO NOT APPLY, thanks****
At GBH, we don’t just do tech, we live it, breathe it, and build it with purpose.
We're the dreamers, the builders, the strategists who turn ideas into digital experiences that actually matter. Whether it’s crafting seamless mobile and web apps, unlocking insights through big data, or rethinking tech strategies, we do it all with impact in mind and belonging at heart.
We’re Geared for Impact. Built for Belonging. And always ready for what’s next.
We are on the lookout for a Senior AI Engineer to build the backend services and asset pipelines behind conversational AI experiences. This engineer owns versioned AI configuration and media-asset workflows, including their integrations with shared services and downstream consumers. This is a software engineering role with AI and media integration responsibilities.
You will be responsible for:
- Build secure authoring APIs and workflows for creating, reviewing, releasing, and retiring versioned AI configurations.
- Build a repeatable pipeline for instructions, behavioral settings, and knowledge artifacts. Track versions and dependencies across releases.
- Integrate with shared registries, knowledge services, evaluation tools, and downstream consumers through documented contracts.
- Build workflows that produce, validate, version, and package approved appearance and voice assets. Record the selected variants in an asset manifest.
- Work with a digital-human specialist to test output compatibility, quality, licensing constraints, and use across device and fallback paths.
- Design asynchronous jobs, retries, idempotency, access controls, observability, release, and rollback for production systems.
- Build unit, contract, and integration tests. Review code, including AI-generated code, before merge.
- Measure pipeline reliability, processing time, storage use, and vendor costs.
Requirements
- Experience building and operating production backend services and asynchronous processing workflows.
- Strong TypeScript or Python skills, API design, automated tests, error handling, and code review.
- Experience integrating LLM or multimodal APIs into production software, including versioned prompts or configurations.
- Experience with cloud storage, artifact versioning, access controls, observability, and deployment in AWS or a comparable cloud.
- Experience integrating external services through APIs or SDKs and managing failures, retries, and vendor dependencies.
- Ability to define and test contracts with other engineering teams.
- Ability to assess data-handling, privacy, and licensing requirements when selecting an integration.
Meet the Team
We’re a company that empowers people. Instead of rules, we have three company values to let you do what you do best. You’re free to be passionate, innovative, collaborative, live a life of integrity, care for those you work with, and delight our customers.
On this team you´ll work with a group of talented professionals such as Hector Aristy.
Benefits
Why Join GBH?
- Our Culture: A friendly, fast-paced and inclusive environment. We rely on an open and empathetic culture that constantly promotes the growth of our team.
- Learning & Development: We do our best to set the best baselines to accelerate your career.
- Benefits & Rewards: We strive to offer competitive, unbiased, and fair rewards for all our people. We empower you to manage your own time and promote flexible working opportunities, along with family-friendly policies.
What Happens once you apply?
Once you have completed your application, we will review your profile and you will hear from us in a period of 5 to 10 days maximum.
Equal Opportunity: The selection process for this position ensures compliance with the principle of non-discrimination by sex, origin (including racial or ethnic), age, marital status, disability, religion or belief, political opinion, sexual orientation, union affiliation, social status, or language.
Know anyone perfect for this role? Refer a friend here.
Similar Jobs
Information Technology • Security • Cybersecurity
Apply established machine learning techniques—including clustering, classification, and anomaly detection—to ICS/OT cybersecurity data. Integrate model outputs into batch and near-real-time pipelines, evaluate third-party models, maintain reliable data contracts and observability, and troubleshoot production issues such as data drift and output quality. Collaborate with AI engineers, data engineers, and product teams while clearly communicating model behavior, uncertainty, and downstream use.
Top Skills:
DockerKubernetesPythonRustScikit-LearnSQL
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Defines and operationalizes technical readiness patterns for external, customer-facing AI systems. Reviews architectures for security, privacy, identity, authorization, runtime, and telemetry standards; partners with governance, security, privacy, product, and engineering teams to close readiness gaps. Extends reusable patterns across MCP, agents, models, and AI APIs, while producing governance evidence, technical documentation, integration guides, and developer portal resources.
Top Skills:
Agent FrameworksCloud-Native Distributed ArchitecturesGenerative AiHealth Data Exchange StandardsIdentity And Access Management (Iam)Large Language Model (Llm) ApisModel Context Protocol (Mcp)OauthOpenid Connect (Oidc)Runtime ObservabilitySoftware Development Kits (Sdks)Telemetry
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, deploy, and monitor production-grade machine learning and deep learning models for healthcare applications. Build scalable data pipelines and automated workflows using Databricks and related platforms, leverage agentic coding tools, and integrate AI services into enterprise applications. Apply responsible AI, governance, security, and monitoring practices while collaborating with software engineers, data architects, and clinical or business stakeholders.
Top Skills:
SparkAPIsCi/CdClaude CodeDatabricksDatabricks GenieDockerHugging FaceKubernetesLlmsNlpOpenai CodexPythonPyTorchRagScikit-LearnTensorFlow
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute


