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