Senior AI Platform Engineer

Infios

Senior AI Platform Engineer developing specification-driven AI-powered solutions at Infios. Leading full lifecycle delivery of applications using AWS AI infrastructure and modern programming languages.

Posted 7/22/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $170,000 - $190,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates deep expertise in the AI software development lifecycle, with a focus on specification-first methodologies and hands-on experience in building production-grade AI applications using Spring AI and AWS infrastructure. Proficient in designing scalable microservices and CI/CD pipelines while effectively communicating technical concepts to diverse stakeholders.

Highest-signal resume keywords

AI Software Development LifecycleSpring AI Application DevelopmentAWS Infrastructure ManagementJava, TypeScript, Python ProficiencyCI/CD Pipeline Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AI Feature SpecificationMicroservices DesignDistributed Systems ArchitectureProduction Application DevelopmentInfrastructure as CodeObservability PracticesDrift DetectionQuality ScoringAcceptance Criteria AuthoringEvaluation Metrics Development

Soft Skills

Analytical SkillsCommunication SkillsMentoringCode ReviewProblem-Solving

Tools & Technologies

Amazon BedrockSageMakerTerraformCloudFormationECSEKSLambdaRDSDynamoDBElastiCache

Industry Keywords

AI ApplicationsLLM Application PatternsPrompt ManagementRAGContext Orchestration

Tech Stack

Tools & technologies

AWSDistributed SystemsDynamoDBJavaMicroservicesPythonSDLCSpringTerraformTypeScript

About the role

Key responsibilities & impact

Define AI feature specifications upfront — including acceptance criteria, evaluation metrics, prompt contracts, and expected behaviors
Own end-to-end AI feature delivery across the full AI SDLC: spec definition, prototyping, development, evaluation, deployment, and production monitoring
Build production-grade LLM and agentic AI applications using Spring AI
Architect and operate AWS AI infrastructure alongside core AWS services
Design and implement scalable microservices and distributed systems in Java, TypeScript, and Python
Build CI/CD pipelines for AI workloads
Drive AI-specific operational practices: observability, drift detection, quality scoring
Communicate technical concepts clearly to both technical and non-technical stakeholders
Mentor engineers, conduct thorough code reviews, and champion engineering excellence

Requirements

What you’ll need

Deep expertise in the AI software development lifecycle with a specification-first mindset
Experience authoring AI feature specs (acceptance criteria, evaluation metrics, prompt contracts)
Track record of shipping AI-powered features through multiple product cycles with engineering rigor
Strong hands-on experience with Amazon Bedrock, Bedrock Agents, Agent Core, SageMaker, and Amazon Q
Solid knowledge of core AWS infrastructure including compute (ECS/EKS, Lambda), databases (RDS, DynamoDB, ElastiCache)
Hands-on experience building production applications with Spring AI
Solid understanding of LLM application patterns (prompt management, RAG, context orchestration)
5+ years of professional software engineering with strong proficiency across Java, TypeScript, and Python
Experience designing and operating distributed systems at scale
Proficiency in CI/CD pipelines, Infrastructure as Code (Terraform, CloudFormation)
Excellent analytical skills and the ability to tackle complex challenges independently
Outstanding written and verbal communication skills

Benefits

Comp & perks

Competitive Medical, Dental, and Vision insurance
401K matching program
Flexible Time Off
11 paid holidays
1 volunteer day per year
A fun, collaborative, and innovative culture where your input matters