Note: The job is a remote job and is open to candidates in USA. ConstructConnect is an innovative company focused on enhancing AI applications across its products and platforms. They are seeking an AI Engineer to design, build, and operate shared AI capabilities for engineering teams, promoting the adoption of AI through practical services and tooling.
Responsibilities
- Design, implement, and maintain shared AI platform components such as services, SDKs, templates, workflows, and reusable libraries that software engineering teams can adopt quickly and safely
- Contribute to engineering patterns and paved paths for AI usage, including model access, prompt handling, evaluation, observability, security, and production support
- Partner with product, application, data, and platform teams to translate AI use cases into scalable technical solutions instead of one-off implementations
- Build and operate reliable, cost-aware AI and ML services on cloud platforms using containerized workloads, managed services, and modern infrastructure practices
- Build and improve internal APIs, developer tooling, and integration patterns that simplify access to AI providers, model endpoints, retrieval services, and supporting data systems
- Support end-to-end workflows for AI and ML use cases, including data preparation, experimentation, deployment, monitoring, and lifecycle management
- Contribute to CI/CD practices for AI-enabled services and ML components, including automated quality checks, security controls, and release guardrails
- Instrument AI workloads with strong observability practices, including metrics, logs, dashboards, tracing, alerting, and cost visibility
- Troubleshoot and resolve issues related to AI and ML deployments, including latency, scalability, integration failures, reliability problems, and cloud cost concerns
- Partner with security, platform engineering, and architecture teams to ensure AI usage aligns with company policies for data classification, access control, privacy, and compliance
- Evaluate emerging AI technologies, frameworks, and vendor capabilities, and share recommendations on where they may fit within ConstructConnect’s engineering roadmap
- Contribute documentation, runbooks, onboarding materials, and reference implementations that help teams adopt AI capabilities with confidence
Skills
- Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent practical experience
- 5–7 years of experience in software engineering, machine learning engineering, platform engineering, or a related area building and operating production systems
- Strong proficiency in at least one modern programming language such as Python, Go, or TypeScript, along with solid software design, debugging, and engineering fundamentals
- Experience building and operating services on a major cloud platform, preferably Google Cloud Platform, including familiarity with compute, storage, networking, and managed services
- Hands-on experience with containers and orchestration technologies such as Docker and Kubernetes
- Experience with CI/CD pipelines and Git-based engineering workflows used to build, test, and deploy services and platform components
- Familiarity with infrastructure-as-code tools such as Terraform for provisioning and managing cloud resources in a repeatable, auditable way
- Familiarity with MLOps concepts and tools used to support model training, evaluation, deployment, and monitoring
- Understanding of modern AI capabilities such as generative AI, embeddings, retrieval patterns, NLP, and related ML concepts, and the ability to apply them responsibly in production environments
- Experience building APIs, services, platforms, or libraries that are consumed by other engineers, with a focus on reliability, usability, and documentation
- Strong foundation in observability and operational excellence, including experience managing service health through metrics, logs, dashboards, and alerting
- Experience working cross-functionally with product, data, infrastructure, platform, and security teams
- Ability to translate technical topics into practical guidance and collaborate effectively in a distributed, remote-friendly environment
- Experience supporting shared AI enablement, developer productivity, or platform engineering initiatives in a multi-team SaaS environment
- Experience with Google Cloud AI and data services such as Vertex AI, BigQuery, or related managed tooling
- Familiarity with AI evaluation frameworks, guardrails, prompt management, model routing, and lifecycle governance
- Experience working with vector search, retrieval-augmented generation, agentic workflows, or orchestration frameworks in production settings
- Exposure to intelligent search, recommendation systems, NLP, or computer vision use cases
- Background working in environments where security, governance, and operational reliability are important to AI adoption
Company Overview