AI Solutions Architect & Tech Lead
New
S
Simple Technology SolutionsAI applications
Remote positionFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- Minimum of 8 years of professional software engineering experience, including at least 3 years leading technical delivery teams and at least 2 years designing and shipping production applications built on large language models
- Required Skills
- AWSPythonSCRUMJiraTerraform
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field; a master’s degree is a plus.
- At least 8 years of professional software engineering experience, including 3 years leading technical delivery teams and 2 years designing and shipping production LLM applications.
- Experience serving as accountable architect for an AWS cloud-hosted application, including security and compliance considerations for a federal or regulated customer.
- Hands-on experience with Kanban and Scrum, backlog grooming and prioritization, and Jira or an equivalent tool.
- Deep working knowledge of Amazon Bedrock, Lambda, API Gateway, IAM, and related AWS networking and storage services.
- Proficiency with Claude Code or comparable agentic coding tools, prompt and context engineering, and designing agent and skill libraries.
- Strong grounding in use-case-driven requirements, spec-driven development, and test-driven development.
- Ability to write production code in at least one modern language; Python or TypeScript preferred, and ability to review Terraform infrastructure as code.
- Familiarity with FedRAMP, NIST 800-53, CJIS, the RMF, and the ATO process.
- AWS Certified Solutions Architect – Associate or higher and Claude Certified Architect – Foundations (CCAR-F), to be earned within 12 months of hire.
Responsibilities
- Lead technical delivery of federal AI application projects as the accountable architect and day-to-day tech lead.
- Establish projects using the STS SDLC for AI App Development and tailor its phases, gates, and templates.
- Design generative AI architectures, including retrieval-augmented generation, agentic workflows, and client-system integrations; document decisions.
- Choose between the OpenCORA chassis, AWS-native services, and agentic development tooling for each project.
- Run agile delivery using Kanban or Scrum, and own backlog grooming and prioritization.
- Orchestrate shared agents and skills across developer, tester, and release-manager roles, keeping use cases, mockups, and specifications as the source of truth.
- Gather early feedback from end users and adjust scope and priorities based on what is learned.
- Communicate project status, risks, trade-offs, and recommendations to clients.
- Enforce test-driven development, infrastructure as code, and the DEV/TST/STG/PRD promotion path; mentor team members and improve the SDLC.
- Contribute to proposals, demonstrations, and technical discussions with prospective federal customers.
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