Asks for

The ad says“Strong proficiency in full-stack web development technologies such as Python, FastAPI, Docker, AWS”
The ad says“Workers & queues: Stand up a reliable background job platform with Celery + Redis (scheduling, retries, idempotency, backoff, result stores).”
The ad says“Experience working with LLMs such as GPT, Claude and Gemini to create LLM-based workflows, RAG Pipelines and agentic solutions. (Either formally or through projects/experimentation)”
The ad says“Strong proficiency in full-stack web development technologies such as Python, FastAPI, Docker, AWS”
The ad says“Strong proficiency in full-stack web development technologies such as Python, FastAPI, Docker, AWS”
The ad says“Experience working with LLMs such as GPT, Claude and Gemini to create LLM-based workflows, RAG Pipelines and agentic solutions. (Either formally or through projects/experimentation)”
The ad says“Experience working with LLMs such as GPT, Claude and Gemini to create LLM-based workflows, RAG Pipelines and agentic solutions. (Either formally or through projects/experimentation)”
The ad says“Agent deployment: Package LLM/RAG agents (e.g., LangGraph/LangChain) into production service.”
The ad says“Agent deployment: Package LLM/RAG agents (e.g., LangGraph/LangChain) into production service.”
The ad says“Experience working with LLMs such as GPT, Claude and Gemini to create LLM-based workflows, RAG Pipelines and agentic solutions. (Either formally or through projects/experimentation)”
The ad says“Frontend touchpoints: Contribute to our Next.js frontend where necessary.”
The ad says“Data layer: Model clean schemas and access patterns for Postgres; use Redis for caching and rate-limiting; integrate vector DBs (Pinecone).”
The ad says“Data layer: Model clean schemas and access patterns for Postgres; use Redis for caching and rate-limiting; integrate vector DBs (Pinecone).”
The ad says“Strong proficiency in full-stack web development technologies such as Python, FastAPI, Docker, AWS”
The ad says“Experience working with LLMs such as GPT, Claude and Gemini to create LLM-based workflows, RAG Pipelines and agentic solutions. (Either formally or through projects/experimentation)”
The ad says“Workers & queues: Stand up a reliable background job platform with Celery + Redis (scheduling, retries, idempotency, backoff, result stores).”

Why you should join us:

Solstice is redefining how life sciences organizations commercialize their therapeutics. We are building a commercial engine that allows pharmaceutical marketers to launch campaigns at 100x the speed.

Rapid growth: Over the past year, we have been working with some of the top life sciences manufacturers and are working with over 50+ pharma brands.
Frontiers of technology: We’re building applications and rapidly iterating technical approaches at the frontiers of AI, experimenting with LLMs and new frameworks. We are incorporating new, advanced frameworks to our solution to better define the possibilities of pharmaceutical marketing.
Top-tier investors: We’ve raised from investors like Transformation Capital, Twelve Below, Virtue and the founders of Datavant, Commure, and Paradigm to supercharge our growth and build an elite team of engineers and operators.

Building anything great requires commitment and dedication. We’re looking for someone who has the fire to prove others wrong

About the role

We’re building Solstice to automate compliant, reference-backed pharma marketing. As a founding full-stack engineer, you’ll own core parts of the application stack, designing APIs, background workflows, and deployment pipelines, and you’ll be responsible for packaging and shipping LLM “agents” to production. Beyond development, you will be collaborating closely with co-founders Yiwen and Aris on all facets of the startup as we grow Solstice in the coming years as we ship fast, safe, and observable systems.

What you’ll be working on

Backend services & APIs: Build and harden FastAPI services; design clean interfaces for ingestion, retrieval, annotation, and compliance checks.
Workers & queues: Stand up a reliable background job platform with Celery + Redis (scheduling, retries, idempotency, backoff, result stores).
Agent deployment: Package LLM/RAG agents (e.g., LangGraph/LangChain) into production service.
Cloud & infra: Ship to AWS, manage secrets, networking, autoscaling, and cost controls.
Integrations: Building robust, enterprise integrations with cloud platforms such as Veeva Promomats, Adobe, and Figma.
Pipelines & files: Orchestrate file processing (PDFs, images), OCR, embedding pipelines, and metadata enrichment at scale (S3-first design).
Data layer: Model clean schemas and access patterns for Postgres; use Redis for caching and rate-limiting; integrate vector DBs (Pinecone).
Frontend touchpoints: Contribute to our Next.js frontend where necessary.

Some ideal traits we’re looking for

Engineering chops. Relevant experience building systems & deploying enterprise-grade products
Independent thinking. While we believe specific skills can be taught, we need someone who has the ability to make decisions and drive results on their own.
Strong proficiency in full-stack web development technologies such as Python, FastAPI, Docker, AWS
Experience working with LLMs such as GPT, Claude and Gemini to create LLM-based workflows, RAG Pipelines and agentic solutions. (Either formally or through projects/experimentation)
Superb communication and collaboration skills. We believe in direct communication and willingness to provide as well as accept criticism.
Unreal work ethic. Diamonds were not made overnight.

Benefits:

Health, dental, and vision insurance
Ground-floor equity opportunity
Visa sponsorship (O-1, H-1B, TN) available
Unlimited PTO
401(k) + 4% company match
In-office lunches 5 days/week
Professional growth stipend
Relocation support
Work in a high-velocity, high-impact environment

Competitive NYC Compensation

This role offers a highly competitive NYC salary in the $160,000–$275,000 range, calibrated to reflect experience, seniority, and the level of ownership you’ll take on as part of the early team. We benchmark against top-tier startups and established tech companies to ensure our compensation is both fair and compelling, and we maintain flexibility at the upper end of the range for exceptional candidates who can meaningfully accelerate our product and engineering roadmap.