[Remote] Digital AI engineer- AWS cloud
Note: The job is a remote job and is open to candidates in USA. Envision Technology Solutions is seeking a Senior AI Engineer to work within their Digital Engineering organization. The role focuses on designing and deploying complex agentic AI systems and requires a strong software engineering background with hands-on experience in AI solutions.
Responsibilities
- Design, build, and deploy complex agentic AI and multi-agent systems that deliver autonomous intelligence across digital engineering workflows
- Develop autonomous AI agents and web-based chatbots that integrate into web-based digital engineering platforms and enterprise applications
- Build and orchestrate end-to-end LLM and agentic workflows — RAG pipelines, multi-agent orchestration, tool/function calling, planning and reasoning loops, prompt engineering, evaluation, and guardrails
- Architect and implement frameworks for autonomous, web-based digital engineering — agents that can plan, execute, and iterate on engineering tasks with human-in-the-loop governance
- Integrate AI agents and services into existing Python / Java applications and AWS-based platforms
- Operationalize agents, models, and pipelines (MLOps / LLMOps) — CI/CD, monitoring, orchestration, performance, cost, and reliability at scale
- Collaborate directly with client engineers, architects, and stakeholders to translate business needs into working, autonomous software
Skills
- 8–12 years of professional software engineering experience, including 2+ years building and deploying production AI/LLM solutions (production systems, not notebooks or POCs)
- Strong, hands-on engineering background — production-grade Python is essential; comfortable working in a Java codebase
- Demonstrated, hands-on experience building agentic AI and multi-agent systems — autonomous agents, multi-agent orchestration, and agent frameworks (e.g., LangGraph, CrewAI, AutoGen, or equivalent)
- Experience developing AI agents and web-based chatbots integrated into web applications and digital platforms
- Deep hands-on command of the modern AI/LLM toolset — LLM APIs and frameworks (e.g., LangChain / LlamaIndex), RAG, vector databases, embeddings, tool/function calling, prompt engineering, and evaluation
- Strong AWS experience — building and deploying on cloud (e.g., compute, storage, serverless, and AWS AI/ML services such as Bedrock / SageMaker)
- Experience with hyperscaler AI/cloud services and integrating them into enterprise applications
- Solid software engineering fundamentals — APIs, microservices, version control, testing, and CI/CD
- Must remain actively hands-on — recent, demonstrable coding experience (not solely architecture or management in recent years)
- Experience as a AI Engineer or in a client-facing, embedded delivery model
- Experience building autonomous / agentic digital engineering capabilities (AI agents that assist or automate the software development lifecycle)
- MLOps / LLMOps tooling and practices for agent and model operations
- Healthcare / payer or regulated-industry experience (data privacy, PHI / PII handling)
- Familiarity with responsible / secure AI practices — governance, guardrails, and human-in-the-loop controls for autonomous systems
Company Overview
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