Our client is in need of a Full Stack Developer. They will be hands on in AI Systems, designing, developing, and deploying production-grade AI applications across our internal operations and client offerings. This role will be building end-to-end solutions that leverage LLMs, agentic AI architectures, multimodal models, and conversational systems.
The ideal candidate is a highly capable full stack engineer with demonstrable experience delivering AI-powered software products from concept through production. While prior experience in the pharmaceutical or biotech space is a plus, it is not required.
You will work closely with our Architects and AI integration Leads, cross-functional consulting teams, and client stakeholders to deliver robust, scalable AI solutions.
Key Responsibilities
1. Internal AI Systems Development
2. Off-the-Shelf Product Development
3. Client Solution Engineering
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Qualifications
Required:
- 7+ years of professional software development experience, with strong proficiency across both front-end and back-end development.
- Proven experience building AI-enabled applications, including:
- Large Language Model (LLM) integration
- Agentic/automated systems
- Chatbots and conversational interfaces
- Retrieval-augmented generation (RAG) systems
- Model orchestration frameworks (e.g., LangChain, LlamaIndex, DSPy)
- Strong command of modern full stack technologies such as:
- Back end: Python, Node.js, FastAPI, PostgreSQL, MongoDB, Django, Flask, Express
- Front end: React, Next.js, Typescript, Tailwind, Vue, or similar
- Databases: PostgreSQL, MongoDB, vector databases (Pinecone, Weaviate, Chroma, Qdrant)
- Cloud & infrastructure: AWS, Azure, GCP, containerization, CI/CD, Docker, Git, CI/CD
- Ability to independently architect systems, write production-quality code, and manage full SDLC execution.
- Experience working in fast-paced environments with shifting priorities and rapid prototyping need
Preferred:
- Experience developing solutions for the pharmaceutical or biotechnology industry, including regulated environments.
- Familiarity with industry-relevant frameworks such as GxP, CFR Part 11, or validated system deployment (not required but advantageous).
- Experience building data pipelines, ETL/ELT workflows, or analytics platforms.
- Prior consulting experience or experience engaging with client stakeholders.