Senior AI Solutions Developer

Summary:

We are seeking a highly motivated and experienced Sr. AI Solutions Developer who operates with high autonomy, owns pre-implementation decisions, enforces OWASP and cost-first discipline, and elevates the team's technical baseline through mentorship and shared tooling. As a Sr. AI Solutions Developer Your primary outputs are production-grade AI systems, architectural decisions the team can build on, and a documented, reusable knowledge base. You are accountable for enforcing the full OWASP LLM Top 10 mitigation stack and STRIDE threat modeling for secure coding.

Job Details:

Work from home

Monday to Friday | 9 AM to 6 PM

Responsibilities:

• Lead AI Solutions pre-implementation review: model selection, cost benchmarking, hosting strategy, prototype trade-offs documented before any build begins

• Architect and implement LLM pipelines: prompt engineering, RAG, structured output, tool use, multi-agent flows

• Design and build REST APIs and data pipelines connecting AI components to Knit and client systems

• Own repo-level AI configuration, shared prompt libraries, agent configs

• Conduct code reviews with written feedback; mentor Junior developers; set and document best practices

• Review SNS/SQS message contracts and integration impact before any cross-service AI merge

• Lead OWASP LLM Top 10 (2025) red-team testing on every project before production release

• Ensure STRIDE threat model is complete for every new AI system, covering data poisoning, prompt injection, model extraction, and excessive-agency risks

• Collaborate with cross-functional teams to gather requirements and propose AI-based solutions that address business needs and drive innovation.

• Stay abreast of emerging AI technologies and industry trends to identify opportunities for enhancing the organization's AI capabilities.

• Evaluate the effectiveness of AI solutions, continuously refining and optimizing them to ensure optimal performance.

• Develop comprehensive documentation for AI solutions, including technical specifications for AI features, LLM APIs, ML Libraries, vector stores, etc.

• Serve as an AI evangelist, promoting the understanding and adoption of AI technologies across the organization through presentations, workshops, and training sessions.

• Provide technical support and troubleshooting for AI implementations, ensuring the prompt resolution of issues and minimal disruption to users.

Qualifications:

• Bachelor’s degree in computer science, Engineering, or a related field. Advanced degrees are highly desirable.

• 4+ years professional software engineering/development, with 2+ years focused on production AI/ML or LLM integration

• Deep Python fluency, i.e. FastAPI or equivalent backend frameworks for production AI services

• Hands-on LLM API experience: Anthropic Claude, OpenAI GPT-4, or equivalent — including structured output, tool use, and agentic patterns

• Solid RAG implementation: chunking strategies, vector stores (Pinecone, Weaviate, pgvector), embedding models, retrieval validation

• Document intelligence: OCR pipelines, PDF extraction (PyMuPDF, pdfplumber, AWS Textract, Docling)

• AWS services: Lambda, S3, Bedrock, SageMaker or equivalent cloud AI platform

• OWASP LLM Top 10 (2025) compliance. Can identify, mitigate, and red-team test all 10 risks in production AI systems

• OWASP ASVS Level 2 secure coding application to API design, authentication, and data handling

• STRIDE threat modeling for AI systems covering data poisoning, prompt injection, model extraction, excessive agency

• Model/API selection for choosing the right model tier for the task (cost-performance fit, not default-to-best)

• Cost-per-request benchmarking with documented analysis extrapolated to 6–12 months at projected scale

• Hosting strategy, e.g. serverless vs self-hosted decision with infrastructure cost trade-off

• Prototype trade-off report, ex. 2–3 model options tested with documented accuracy, latency, and cost results

• Strong knowledge of AI technologies, including machine learning, natural language processing, and computer vision.

• Exceptional problem-solving and analytical skills, with a proven ability to design and implement innovative solutions.

• Excellent communication and interpersonal skills, with the ability to effectively collaborate with diverse teams and convey complex technical concepts to non-technical stakeholders.

Nice to Have:

• Multi-agent frameworks: LangGraph, CrewAI, AutoGen, or custom orchestration

• ISO 42001 AI Management System controls

• EU AI Act risk classification and technical documentation

• Philippines DPA 2012 and GDPR Article 25 (privacy by design) applied to AI system architecture

• Amazon Connect or contact center AI integration experience

• MCP (Model Context Protocol) server development

• SBOM/AIBOM generation using CycloneDX or SPDX