Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Oct 6, 2026. Ltm scores B on the Alion truth index.
Role Overview
We are looking for an experienced AI Engineer Tech Lead to support strategic modernization initiative The role will focus on designing building and leading productiongrade agentic AI capabilities that enhance claim professional workflows reduce cycle time automate repetitive tasks and enable scalable AI delivery across the value stream The selected candidate will work closely with technology leads engineering teams product stakeholders and delivery teams to develop AInative solutions using LLM based reasoning multiagent orchestration RAG patterns vector search prompt management AI evaluation observability and secure deployment practices
Key Responsibilities
Lead the design and implementation of AIfirst and agentic AI solutions for the
strategic modernization
Build and integrate LLMbased reasoning capabilities into claim and
operational workflows to improve efficiency and reduce manual effort
Design and implement multiagent orchestration patterns using enterprisestandard
AI frameworks
Develop scalable Pythonbased AI services APIs MCP servers and
automation components
Implement RAGbased solutions using embeddings vector stores and
enterprise knowledge sources
Create and manage versioncontrolled prompts using prompt management
practices
Establish AI quality validation through response evaluation grounding checks
and output testing
Ensure AI security controls including PII detection guardrails and prompt
injection defense
Collaborate with engineering architecture product and delivery teams to
convert AI concepts into productionready capabilities
Provide technical leadership to developers and engineers working on AInative
use cases
Support CICD infrastructure automation observability and productionreadiness
practices
Partner with stakeholders during technical screening solution walkthroughs
and onboarding into PI delivery cycles
Required Technical Skills
AI Agentic AI
Strong handson experience in LLM application development
Agentic AI design and implementation experience
Multiagent orchestration experience
Prompt engineering and prompt lifecycle management
AI evaluation and response quality validation
Experience with secure AI design including guardrails and PII handling
Preferred AI Stack Alignment
AWS Bedrock
AgentCore
Claude Sonnet
AWS Strands SDK
Amazon Titan Embeddings v2
Bedrock Prompt Management
Bedrock Guardrails
AgentCore Evals Braintrust
Engineering Platform Skills
Strong programming expertise in Python
Experience building APIs using FastAPI
Knowledge of TypeScript and React for AIenabled UI integration
Experience with GitHub and GitHub Actions
Infrastructure automation exposure using Terraform or AWS CDK
Experience with observability and tracing using OpenTelemetry
Familiarity with monitoring AI agents for latency token cost execution steps and
reliability
Working knowledge of Dynatrace ELK and OTel is preferred
Functional Domain Expectations
Ability to understand claim lifecycle workflows and identify AI automation
opportunities
Experience translating business problems into AIenabled workflow solutions
Ability to support modernization initiatives across assisted surfaced and
automated AI maturity phases
Strong understanding of enterprisegrade delivery expectations not just
prototype development
Ability to work in SAFe PIbased delivery environments
Modernization objectives include integrating LLMbased reasoning into claim
professional workflows automating repetitive claim tasks using multiagent
orchestration delivering productiongrade agentic AI and building a durable AI delivery
model that scales across the value stream
Mandatory Qualifications
8 years of software engineering experience
3 years of handson AI ML LLM engineering experience
Strong Python development background
Practical experience with LLMbased application architecture
Experience building APIs automation services or AInative backend services
Experience with cloudnative AI services preferably AWS
Strong understanding of RAG embeddings vector search and prompt
management
Experience with CICD Gitbased development and production deployment
practices
Strong communication skills and ability to work with distributed engineering
teams

