About the role
We build predictev™, an AI-driven audience intelligence platform used by pharma brand and marketing teams. The platform is live, the client list is growing, and the asks change weekly — a new brand, a new data cut, a new agent capability needed with a short turnaround.
We are looking for a senior engineer who can land inside an existing codebase and be productive in days. You will ship features on top of predictev™ under real client deadlines, make the call on what is worth building properly versus what needs to work by the deadline, and raise the technical bar for a small team of engineers and data scientists around you.
The differentiator we care most about: you have built for pharma commercial teams before, and you already understand what they are asking for. What you'll do
Ship features on an existing platform — extend the predictev™ agent framework, data pipelines, and application layer without breaking what is already in production
Turn client asks into working software fast — take an ambiguous request from a brand team and get a usable version in front of them in days, then iterate on real feedback
Build and tune agentic AI features — retrieval, text-to-SQL, classification, and reasoning agents, with evals and observability rather than vibes
Debug and stabilize — diagnose quality, latency, and accuracy issues across the stack and fix root causes, not symptoms
Guide more junior engineers — code review, pairing, patterns, and unblocking, without needing formal authority to be listened to
Pivot fast — priorities shift when a client or pitch shifts; you re-scope quickly and say clearly what moves out
Make pragmatic architecture calls independently — balancing speed against technical debt, and flagging the tradeoff instead of hiding it
What we're looking for
5+ years of professional software development experience
Pharma or life sciences commercial experience — you have built analytics, data, or marketing products for pharma clients and understand how brand and medical teams work
Proven speed on an existing codebase — you can read unfamiliar code, find the seam, and ship a change safely in the first week
Hands-on AI-driven development — coding agents, LLM APIs, and AI-assisted workflows as a core part of how you build, not an experiment
Comfort with client-driven ambiguity — requirements arrive incomplete and change mid-build; you ask two sharp questions and start
Technical leadership instincts — you make other engineers better through review and example, and you escalate early rather than quietly slipping
Strong written communication — remote, asynchronous, and reliable against milestones
Strong judgment about when to optimize for speed versus robustness
Domain background we are prioritizing
The strongest candidates have built for pharma commercial teams from inside a data, analytics, or consulting organization. Backgrounds we specifically want to see:
Pharma data and analytics firms — IQVIA, ZS, Veeva, Komodo Health, Definitive Healthcare, Symphony, or similar
Pharma marketing and media agencies — HCP and DTC campaign work, omnichannel planning, or brand strategy support
Working fluency in the vocabulary — HCP segmentation and targeting, patient journey, NBRx/TRx, claims and script data, MMM and attribution, field and speaker program data
Compliance instincts — PII and PHI handling, HIPAA and privacy constraints, and what makes a client security team comfortable
Tech stack
Python — production services and data work; FastAPI or similar
SQL and PostgreSQL — strong SQL is non-negotiable; large behavioral datasets, query performance, and schema design
AI / LLM tooling — LLM APIs (Anthropic, OpenAI), agent frameworks (LangChain / LangGraph or similar), RAG and embeddings, prompt engineering, and an eval-first mindset
LLM observability — Langfuse, LangSmith, or equivalent tracing and evaluation tooling in production
Frontend — React and TypeScript, enough to build and fix the application layer end to end
Cloud and infra — AWS (or GCP), Docker, and CI/CD; comfortable deploying your own work
AI dev workflow — fluent with AI coding assistants and agentic dev tools (Claude Code, Cursor, Copilot, and similar)
Bonus points
Background in fast-paced, startup-style or product-launch environments
Experience building production agentic systems with observability and evals
Exposure to BI and reporting layers (Power BI, Tableau) and to client-facing data delivery
Experience supporting security reviews, penetration test remediation, or client IT assessments
Experience:
5+ years engineering, with pharma / life sciences exposure
Numbers & Facts
Location
Philadelphia, PA (Remote)
Skills
Application Programming Interface (API)unmatched
Artificial Intelligence (AI)unmatched
Biologyunmatched
Biotech and Pharmaceuticalunmatched
Brand Marketing (Branding)unmatched
Brand Strategyunmatched
Business Intelligenceunmatched
Campaignsunmatched
Code Reviewsunmatched
Consultingunmatched
Customer Relationsunmatched
Data Analysisunmatched
Data Managementunmatched
Data Scienceunmatched
Data Setsunmatched
Database Designunmatched
Debugging Skillsunmatched
Establish Prioritiesunmatched
HIPAA (Health Insurance Portability and Accountability Act)unmatched
Healthcareunmatched
Identify Issuesunmatched
Machine Toolunmatched
Marketingunmatched
Penetration Testingunmatched
Pharmaceutical Analysisunmatched
Pharmaceutical Dataunmatched
PostgreSQLunmatched
Power BIunmatched
Product Engineeringunmatched
Product/Service Launchunmatched
Production Systemsunmatched
Python Programming/Scripting Languageunmatched
SQL (Structured Query Language)unmatched
Scripting (Scripting Languages)unmatched
Security Attacksunmatched
Software Developmentunmatched
Startupunmatched
Tableauunmatched
Technical Leadershipunmatched
Time Managementunmatched
Writing Skillsunmatched
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