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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and deploying production software using Python and AWS services, particularly Amazon Bedrock. Capable of integrating AI solutions, collaborating with clients, and ensuring quality through automated testing and deployment pipelines.
Highest-signal resume keywords
Python DevelopmentAWS LambdaAmazon BedrockAutomated TestingClient Collaboration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Production Software DevelopmentAPI IntegrationAI Solution ImplementationData Pipeline DevelopmentVersion Control
Soft Skills
Client EngagementMentoring
Tools & Technologies
Amazon SageMakerAWS IAMBedrock AgentCoreBedrock Knowledge BasesDeployment Pipelines
Certifications & Qualifications
AWS Solutions Architect – ProfessionalAWS Solutions Architect – AssociateCertified Generative AI Developer
Industry Keywords
Financial ServicesConsumer MarketsTechnologyMediaTelecommunications
Tech Stack
Tools & technologiesAWSJavaPythonTypeScriptGo
About the role
Key responsibilities & impact- Map client workflows with business users and process owners; define use cases, delivery backlogs, and measurable acceptance criteria
- Build working prototypes and test them against representative client data and user feedback
- Develop agent workflows, retrieval and grounding, tool calling, and APIs using Python, Amazon Bedrock, Bedrock AgentCore, and Bedrock Knowledge Bases
- Integrate AI solutions with client systems using AWS Lambda, Amazon SageMaker, and approved data sources, with authentication and permission-aware access through AWS IAM
- Write automated tests and AI evaluations; build deployment pipelines, monitoring, and error handling
- Assess solutions against release criteria for quality, safety, latency, reliability, and cost
- Configure Amazon Bedrock Guardrails and collaborate with security, privacy, and risk specialists on technical controls, audit evidence, and human review steps
- Co-build with client engineers and provide documentation, runbooks, and knowledge transfer
- Contribute reusable components, evaluation assets, and implementation patterns to the engineering community within client confidentiality and IP obligations
- Support pursuits through technical demonstrations, feasibility assessments, and delivery estimates
- Spend approximately 70% of time building on Amazon Bedrock and related AWS services and 30% working with client users and technical teams
Requirements
What you’ll need- 4+ years of experience building and deploying production software
- 3+ years of experience writing Python in production
- 3+ years of experience building on AWS, including AWS Lambda and AWS IAM
- 1+ year of experience building applications that use LLMs, including retrieval, structured outputs, tool calling, or agent workflows
- Experience working directly with clients or business stakeholders to clarify requirements and demonstrate progress
- Experience with version control, automated testing, and deployment pipelines
- Ability to travel up to 70%, typically Monday through Thursday, including on-site work with clients
- Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience
- Delivery experience with Amazon Bedrock, Bedrock AgentCore, Bedrock Knowledge Bases, Bedrock Guardrails, or Amazon SageMaker
- Experience building at least one production application on AWS that calls a foundation model through Amazon Bedrock or another model API
- Experience building evaluation datasets, adversarial tests, or AI observability for a production system
- Experience with enterprise search, document processing, or structured and unstructured data pipelines
- Experience building tools or integrations using APIs or Model Context Protocol
- Proficiency in a second language such as TypeScript, Java, or Go
- AWS certifications, such as Solutions Architect – Professional or Associate, or Certified Generative AI Developer
- Experience in financial services, consumer markets, or technology, media, and telecommunications
- Experience mentoring engineers
Benefits
Comp & perks- Annual discretionary bonus
- Medical insurance
- Dental insurance
- Vision insurance
- 401k
- Holiday pay
- Vacation
- Personal and family sick leave
- Professional development opportunities
- Flexible work arrangements
- Competitive compensation