aws-ecs jobs in San Diego

Design, develop, and maintain infrastructure-as-code and CI/CD pipelines using Terraform, Ansible, and GitLab to automate provisioning and deployments across environments. Perform systems analysis to document functions and define integration interfaces; manage Linux-based and Windows infrastructure including Active Directory, VMware, and container orchestration (Docker, Kubernetes, OpenShift, AWS EKS/ECS).…See more Maintain Jira tracking and participate in SAFe Agile ceremonies. Requires 10 years of software development experience, DevSecOps expertise, DoD 8570 IAT Level II certification, and ability to travel 25% including possible U.S. Navy ship deployments.

Incedo seeks a .NET Architect with 12–18 years of IT experience to lead enterprise-scale digital banking solutions on AWS. The role requires designing cloud-native, microservices-based architectures using .NET Core/.NET 6+, establishing architecture standards, conducting code and design reviews, and ensuring compliance with banking regulations.…See more The candidate must hold an AWS Solutions Architect certification, mentor engineering teams, and drive CI/CD, DevOps, and observability best practices across mission-critical applications.

This Technical Lead role focuses on architecting, developing, and deploying production-grade Agentic AI solutions on AWS using .NET/C#. The ideal candidate will have hands-on expertise in LLMs, generative AI, RAG, prompt engineering, and agent frameworks (LangChain, LangGraph, Semantic Kernel, AutoGen), combined with strong .NET enterprise development and AWS cloud-native skills.…See more Responsibilities include taking AI solutions from POC to production, designing microservices and REST APIs, and ensuring AI evaluation, monitoring, observability, and governance. Technical leadership, stakeholder management, and system design fundamentals are essential.

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and customer experiences. Responsibilities include implementing end-to-end AI/ML pipelines using AWS services (SageMaker, Lambda, ECS/EKS), feature engineering with Snowflake, model fine-tuning and testing, and monitoring production performance.…See more The role requires 3+ years of AI/ML experience with 1–2 years in generative AI or LLMs, hands-on cloud deployment experience, and proficiency in Python, PyTorch, TensorFlow, or Hugging Face Transformers.

Senior Enterprise Applications Developer responsible for designing, delivering, and supporting complex enterprise software, integrations, data solutions, and automation across cloud and on-premises environments. Requires 7+ years of progressive experience with advanced Python proficiency, hands-on expertise in REST APIs, ETL/data pipelines, CI/CD practices, and AWS or Azure cloud-native development.…See more Must demonstrate ability to lead solution design from requirements through production support, with experience in workflow automation, AI/LLM integrations, and compliance frameworks (HIPAA, SOC 2, SOX). Strong emphasis on security, governance, architecture, and cross-functional collaboration with technical teams and business leaders.

AI Architect role requires designing and delivering enterprise-scale AI/ML solutions on AWS, with 5–7 years of cloud experience and 2–3 years hands-on with LLMs, agentic frameworks, and AI/ML services. The position demands deep expertise in AWS AI services (Bedrock, SageMaker, Kendra), orchestration frameworks (LangChain, LangGraph), RAG pipelines, MLOps tooling, and responsible AI principles.…See more Candidates must architect scalable, cost-optimized solutions integrating AI with cloud infrastructure, data platforms, and microservices, and communicate complex technical concepts to executive and technical audiences.

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and internal workflows. The role involves implementing end-to-end AI pipelines using AWS services (SageMaker, Lambda, ECS/EKS, S3), building feature engineering workflows in Snowflake, and collaborating with cloud and MLOps teams.…See more Candidates need 3+ years of AI/ML engineering experience with 1–2 years focused on generative AI or LLMs, proficiency in Python and frameworks like PyTorch or Hugging Face Transformers, and hands-on cloud deployment experience. The position requires monitoring model performance, ensuring security and compliance, and supporting AI architecture reviews.