AI Engineer SR (CHR/AI-20250812)
Remote
Celara /
Contract /
Remote
We're looking for a Senior AI Engineer - Product Team Lead — a hands-on technical leader who thrives at the intersection of cutting-edge AI and product engineering. You'll architect solutions from client requirements to production deployment, lead technical decisions, and help scale our engineering team.
This is a high-ownership role for someone who combines strong engineering fundamentals with product thinking, client communication skills, and the ability to drive complex technical projects from concept to delivery. You'll work directly with clients, mentor engineers, and shape both our technical foundation and product direction.
You thrive in startup environments where you can wear multiple hats, move fast, and have direct impact on company growth. This role has clear potential to grow into leading our entire engineering team as we scale.
What You’ll Do
- 1. Lead Product Engineering & Technical Architecture
- Drive end-to-end solution design from client requirements through production deploymentMake critical architectural decisions for scalable, maintainable AI systemsBalance technical excellence with business needs and delivery timelinesOwn technical roadmaps and coordinate cross-functional product development
- 2. Client-Facing Technical Leadership
- Work directly with clients to extract requirements, provide technical guidance, and manage expectationsTranslate complex AI capabilities into clear business value propositionsLead technical discussions, demos, and solution presentationsPush back constructively on unrealistic requests while proposing viable alternatives
- 3. Build & Deploy Production AI Systems
- Develop and deploy Python-based GenAI solutions using modern frameworks (LangChain, LlamaIndex, OpenAI APIs)Design and implement production-ready RAG systems, vector search, and LLM workflowsBuild robust APIs and integrate AI models into scalable production systems (FastAPI, Flask, Django)Deploy and manage AI systems on cloud platforms (AWS, GCP, Azure) with MLOps best practicesOptimize for performance, cost-efficiency, and reliability across distributed cloud environments
- 4. Team Leadership & Mentorship
- Mentor AI engineers and foster a collaborative, high-performance engineering cultureDrive technical direction, code quality standards, and engineering best practicesPlan resource allocation and coordinate technical projects across the teamHelp scale the engineering team as the company grows
Must-Have Skills
- Product Engineering & Architecture5+ years of Python engineering experience with strong software architecture skillsAbility to design scalable systems and make technical decisions that balance performance with business needsExperience building and deploying production APIs using FastAPI, Flask, or equivalentSolid software engineering habits: clean code, version control, CI/CD, testing
- Leadership & Client CommunicationStrong communication skills with ability to work directly with clients and extract requirementsExperience mentoring and guiding engineers, fostering a product-driven development cultureProduct mindset with ability to balance technical excellence and business valueStartup mentality: proactive, comfortable with ambiguity, and eager to lead technical projects
- Software Engineering & DeploymentCloud computing expertise (AWS, GCP, Azure) for scalable AI deploymentsDevops/MLOps best practices for model deployment, monitoring, and maintenanceExperience with LLM cost optimization, containerization, and infrastructure-as-code
- Core AI/ML ExpertiseDeep understanding of LLM-based workflows, embeddings, prompt engineering, and RAG systemsExperience with modern GenAI frameworks (LangChain, LlamaIndex, OpenAI APIs)Familiarity with vector databases (FAISS, Pinecone, Weaviate) and model evaluation/selectionExperience working with large-scale datasets, preprocessing, and feature engineering
Why Join us?
- Work on large-scale AI projects with real-world impact
- High autonomy, high-impact role on a lean, ambitious team
- Shape both the product and technical foundation of AI systems
- Fully remote work with flexibility
- Competitive compensation and opportunities for career growth
- Continuous learning, experimentation, and exposure to cutting-edge AI tools
