This resource will be tasked with building and developing a tool for Due Diligence. They need to have both front end and back end development experience as they will be tasked with connecting to multiple different data sources and visualizing this data in the front end. Additionally, they will need experience using AI and building knowledge graphs. If they have experience hosting containerized applications on AWS that would be a plus. The scope of this work will be until the end of the year.
Needs to have experience in Identity Governance and using the Microsoft Graph API to create the security application mentioned in the job description.
Position Requirments:
3-5 years of Full Stack Experience , Computer Science Degree
AWS, Neo4j
AI, Prompt Engineering
IR Domain Expertise
The role
Build four AI tools for pharma BD/S&E analysts into supportable production services, and build the Deal Access Control Center — an Entra ID / Active Directory reconciliation service that governs access to all of them. Three interchangeable full-stack engineers; you move across backend, frontend, the LLM/agent layer, the Microsoft identity stack, and deployment.
What you'll build
- AI tools (BD Deals Engine, Due Diligence, Triage, Landing Page): add test coverage, move secrets to a vault + service accounts, fix CI/CD and dependency pinning, add observability, extend document extraction (PDF/PPT/XLSX/DOCX), enforce an outbound-data guard, and preserve the RAG + citation-verification quality.
- Deal Access Control Center: an idempotent, hourly reconciliation service that reads the deal "tent list", validates + gates entries (CDA, training), provisions deal-scoped Entra/AD security groups (APP-?Deal>-Owner/Editor/Viewer), and writes an immutable audit log. Integrate consumers by push (SharePoint, Teams, VDRs via Microsoft Graph) and pull (AI tools, Dataverse, ARCH at query time).
Technical requirements
Must have:
Languages: Python 3.11+, TypeScript, SQL
Backend: FastAPI (async), server-sent events / streaming
Frontend: React 18, Vite, Node
AI / LLM: LLM app development: agent tool-use loops, prompt engineering, streaming; RAG — embeddings, vector/similarity search, chunking, source grounding
Microsoft identity: Entra ID / Azure AD, Microsoft Graph API, security-group provisioning, SharePoint/Teams automation; RBAC, least-privilege, default-deny
Infra / DevOps: Docker, Kubernetes, CI/CD, secrets management; idempotent scheduled/reconciliation services
Quality: pytest + Vitest/Jest; adding tests to untested code
Experience: 3-5 years full-stack; comfortable owning an unfamiliar codebase end-to-end
Nice to have
Identity governance (IGA — access certification, joiner-mover-leaver, audit logging) · Power Platform / Dataverse (row/column security) · knowledge graphs & Cypher · Claude Code extension points (skills, subagents, MCP connectors) · document parsing (PyMuPDF, python-pptx/docx, openpyxl) · VDR / external-party provisioning · regulated-enterprise deployment (proxy, SSO, internal gateways) · pharma BD / licensing / M&A domain.
Success
Tools are tested, observable, and reproducibly deployed with managed secrets. Access is granted within one hour of a tent-list entry, zero entitlements live outside a deal security group, revocation is immediate, and audit evidence is produced on demand.