Forward Deployment Engineer Devops and AI Development

The team is seeking an Associate Forward Deployment Engineer specializing in DevOps and AI Development. This role is focused on deploying AI solutions into production environments, ensuring reliability and security while working closely with an enterprise client's team. The ideal candidate will transition AI applications from prototype to a robust production state on AWS, leveraging strong CI/CD practices, containerization, and infrastructure automation.

Key Responsibilities:

• Package and deploy AI/LLM applications and agent workflows onto the team AWS infrastructure.
• Build and maintain CI/CD pipelines that ensure safe and repeatable shipping of AI services.
• Containerize services using Docker and manage them on Kubernetes.
• Provision infrastructure as code with Terraform, incorporating necessary identity, security, and networking configurations.
• Set up model and application serving, including integrations with AWS Bedrock and vector database infrastructure.
• Implement observability and cost tracking for AI workloads.
• Integrate AI solutions into existing legacy systems and regulated data environments.
• Automate repetitive deployment and operational tasks.
• Collaborate with client engineers via Teams, Slack, and email, ensuring deployment runbooks are up to date.

Required Qualifications:

• Proven experience in DevOps, platform, or deployment engineering with a focus on production shipping.
• Strong background in CI/CD and release automation.
• Hands-on experience with Docker and Kubernetes in production settings.
• Proficient in Infrastructure as Code and fluent in AWS services.
• Scripting skills for automation using Python and/or Bash.
• Ability to integrate with existing client identity, security, and networking setups.
• In-depth understanding of deploying and running AI and LLM applications in production, including model serving and RAG/vector infrastructure.
• AWS Certified Solutions Architect – Associate or AWS Certified DevOps Engineer – Associate.

Preferred Qualifications:

• Experience deploying within regulated environments with governance and change-management considerations.
• Familiarity with enterprise AI or data platforms such as Databricks, Snowflake, or Palantir Foundry.
• Knowledge of MLOps tooling (MLflow, model registries, feature stores).
• Some experience in Site Reliability Engineering (SRE) or reliability practices.
• Previous customer-facing or forward-deployed work experience.
• Certifications such as Certified Kubernetes Administrator (CKA) or Terraform Associate are advantageous.

Technical Skills & Tools:

• Cloud (AWS): Bedrock, SageMaker, Lambda, ECS, EKS, Step Functions, S3, API Gateway, IAM, CloudWatch.
• Containers & IaC: Docker, Kubernetes, Helm, Terraform, Ansible, CloudFormation.
• CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD.
• AI deployment: LLM/agent serving, inference endpoints, RAG infrastructure, vector databases (Pinecone, pgvector, Weaviate, Qdrant, OpenSearch).
• Observability & cost: OpenTelemetry, Langfuse, Prometheus, Grafana, CloudWatch.
• Security & networking: IAM, secrets management, VPC and network configuration.
• Scripting: Python, Bash, Git.
• Good to have: MLOps (MLflow, model registries, feature stores), Databricks, Snowflake, Palantir Foundry.

What we offer:

• Opportunity to work on cutting-edge AI technologies and solutions.
• Collaborative and dynamic work environment.
• Professional development and growth opportunities.