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Tech Stack
Tools & technologiesPython
About the role
Key responsibilities & impact- Lead and grow the engineering team — hire, mentor, and develop engineers across product, platform, and infrastructure disciplines, building a culture of ownership, craft, and continuous improvement. Build a culture where engineers deeply understand and empathize with customers, not just internal requirements
- Champion AI-native engineering practices.
- Define and own the AI engineering roadmap, aligning technical direction with company and product strategy.
- Oversee architecture and implementation of LLM-driven systems, including retrieval-augmented generation (RAG), chat agents, and semantic search pipelines.
- Champion best practices for model evaluation, and AI feature integration.
- Evaluate, integrate, and optimize LLMs (e.g., GPT, Claude, Llama, Mistral) for production use cases.
- Collaborate with engineering leadership to ensure scalability, performance, and reliability across CoreStory’s Platform.
- Foster a strong culture of experimentation, learning, and innovation across the engineering team.
- Stay ahead of emerging trends in LLMs, RAG architectures, and AI frameworks — translating research into product-ready capabilities.
- Own delivery velocity and execution — establish engineering processes, sprint cadences, and delivery practices that keep teams moving with clarity and confidence — without unnecessary overhead. Driving ownership of customer-facing engineering issues end-to-end
Requirements
What you’ll need- 10+ years of experience in software or AI engineering, including 5+ years in a leadership role.
- Demonstrated experience working directly with customers (e.g., enterprise clients, design partners, or production users) to understand real-world use cases, pain points, and business impact
- A track record of hiring and developing strong engineers, and building team cultures where people do their best work. Proven ability to translate customer needs into engineering priorities, driving urgency, accountability, and high-quality outcomes
- Proven experience leading teams building agentic systems. Expertise in designing and building a from-scratch implementation of an agent network is highly desirable.
- Strong understanding of Agent Harnesses, RAG architectures, embedding pipelines, and tokenization.
- Demonstrated success leading end-to-end delivery of AI features in production environments.
- Excellent communication, collaboration, and leadership skills.
- Deep hands-on expertise with frameworks such as LlamaIndex, LangChain, or similar orchestration tools. (Preferred)
- Proficiency in Python, including libraries such as FastAPI, Claude SDK, DSPy. (Preferred)
- Experience leading AI initiatives in startup or SaaS environments. (Preferred)
- Familiarity with knowledge graphs, and hybrid IR systems. (Preferred)
- Background in LLM evaluation, AI observability, or model performance optimization. (Preferred)
- Passion for continuous learning and experimentation with cutting-edge AI research. (Preferred)
Benefits
Comp & perks- Competitive compensation and equity.
- Flexible, remote-first work environment.
- Opportunity to lead and shape CoreStory’s AI engineering strategy and execution.
- Collaborative, innovation-driven team culture.
- Access to state-of-the-art AI technologies and research.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
AI engineeringsoftware engineeringLLM-driven systemsretrieval-augmented generationchat agentssemantic search pipelinesmodel evaluationAI feature integrationPythonembedding pipelines
Soft Skills
leadershipmentoringcommunicationcollaborationinnovationcustomer empathyteam buildingaccountabilityurgencycontinuous improvement