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