AI Engineer

Before You Apply — A Message from Our Founder

For generations, women have navigated systems never built with them in mind. The gaps in leadership, health, wealth, and opportunity were engineered into the world we inherited—and now, for the first time, we have the tools to build something better. AI gives us the chance to design technology that truly partners with the women and organizations working tirelessly to advance women and girls. Being trusted to do this work is both a privilege and a responsibility, and I am looking for people who feel that responsibility as deeply as I do.

Uplevyl is not a conventional workplace. We have a distinct culture. We exist to create meaningful impact for society, and we hold ourselves to a standard of moving fast while delivering quality that endures. We partner only with those who share our commitment to doing important work, and we build technology that opens doors, expands opportunity, and enables more people to participate and benefit.

We hire only A-players and compensate them accordingly. We do not compromise on talent, and we part ways respectfully when performance does not meet the standards required by our mission. Everyone at Uplevyl wears multiple hats. No task is beneath anyone. Decisions are driven by merit, not hierarchy. We prioritize customers over internal convenience, avoid politics, and maintain zero tolerance for unnecessary bureaucracy.

We move with urgency because the mission demands it. When the work calls for it, we stretch beyond traditional hours—not out of obligation, but out of genuine commitment to building something transformative. We look for people energized by bold problems, people who find meaning in momentum and possibility, and who bring a proactive, high-ownership mindset to everything they do. If you thrive in environments where innovation, purpose, and high standards come together, you will feel at home at Uplevyl.

Key Responsibilities

• Design, develop, and deploy LLM-based AI solutions for scalable community systems.
• Implement advanced RAG architectures, embedding pipelines, and vector databases (Pinecone, FAISS, Qdrant).
• Build multi-agent orchestration frameworks to support adaptive, intelligent workflows.
• Fine-tune, pre-train, and evaluate LLMs for domain-specific applications.
• Integrate AI/ML systems with AWS services such as SageMaker, Bedrock, ECS, and Cognito (or equivalent platforms).
• Collaborate closely with product and community teams to translate use cases into robust AI solutions.
• Ensure ethical AI practices when managing domain-sensitive or private datasets.
• Stay updated on AI research and apply innovations to improve system scalability, efficiency, and performance.

Performance Expectations

• Deliver production-ready AI models and pipelines within agreed timelines
• Demonstrate measurable impact on community engagement and operational efficiency.
• Maintain rigorous standards of ethical AI and data governance.
• Identify bottlenecks in scaling agentic communities and propose proactive solutions.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

Benefits

• Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or related field.
• 4+ years of experience building LLM-based or NLP-driven solutions.
• Proven expertise with RAG architectures, vector DBs (Pinecone, FAISS, Qdrant), and embedding workflows.
• Strong hands-on experience in Python, PyTorch/TensorFlow, LangChain, LangGraph, and Hugging Face Transformers.
• Familiarity with AWS AI/ML infrastructure (SageMaker, Bedrock, ECS, Cognito) or similar cloud stacks.
• Experience handling sensitive datasets with strong ethical AI considerations.
• Demonstrated capability in LLM fine-tuning, pre-training, and evaluation.

Required Skills

• Advanced proficiency in LLMs, RAG pipelines, vector databases, and AI orchestration frameworks.
• Strong engineering fundamentals with ability to build scalable, production-grade AI systems.
• Hands-on experience deploying AI/ML solutions on AWS or equivalent cloud environments.

Cultural & Work-Style Skills

1. Low Ego, High Contribution You collaborate across disciplines, share knowledge openly, and welcome feedback on architecture, code, and decisions. You care more about building the right system than about being “right.”

2. Ownership From Design to Delivery You think beyond tickets. You take responsibility for the full lifecycle of what you build including architecture, implementation, testing, reliability, and iteration. You solve problems end-to-end rather than waiting for perfect specifications.

3. Mission-Driven Urgency With Technical Depth You move quickly when needed, but never at the expense of long-term stability. You can distinguish when to build fast and when to build right and you communicate trade-offs clearly.

4. Agility in Ambiguity You are comfortable building in evolving environments with partial information. You prototype, test assumptions early, reduce dependencies, and find creative paths through constraints.

5. Purpose-Fueled Resilience & Curiosity You stay steady when debugging complex issues, you learn rapidly, and you adapt as the product and architecture evolve. You draw energy from solving meaningful problems and building systems that open doors for millions of women.

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