MidFull TimeENEurope
Index.dev is partnering with StockStory (CNBC / VERSANT) to hire a Senior AI Engineer in Prague.
VERSANT is an independent, publicly traded company that brings together powerhouse brands such as CNBC, MS NOW (formerly MSNBC), USA Network, Oxygen, E!, SYFY, and Golf Channel along with dynamic digital and direct-to-consumer brands such as Fandango, Rotten Tomatoes, GolfNow, GolfPass, and SportsEngine.
StockStory, now part of CNBC under VERSANT, is building the next generation of AI-powered equity research for individual investors. This is a chance to build products that can shape how millions of consumers understand markets and make investing decisions.
We offer the best parts of a startup environment — small team, high ownership, fast execution, and room to experiment — with the backing and stability of VERSANT, an independent publicly traded media company.
As an AI engineer, you will work on both an existing AI product with real user impact and greenfield projects with significant room for exploration. The work spans cutting-edge LLMs, large-scale data systems, financial reasoning, and research tooling, with opportunities to apply ideas from functional programming and graph-based systems where they create real advantage.
You will be joining a team of exceptional engineers, analysts, and investors working at the intersection of AI and public markets. A particularly rare part of this role is the level of direct access to experienced market professionals, including former hedge fund managers and top-tier analysts, whose insights can directly inform how you think about modeling, signals, and product design.
We're looking for a Staff AI Engineer to help build the next generation of AI-powered equity research.
This role is for engineers who are excited by taking LLM capabilities beyond prototypes and turning them into robust product systems that deliver real value in production. It is especially well suited to people who enjoy designing end-to-end workflows, shaping technical direction, and building reusable foundations that help multiple teams move faster.
You will design, build, and ship LLM-powered systems that integrate into new and existing workflows across the platform, spanning orchestration, retrieval, tool use, evaluation, and operational safeguards. You will also help define the engineering standards and architectural patterns that make these systems reliable, scalable, and maintainable over time.
This role sits within a small and growing, high-caliber team where individuals are expected to operate with a high degree of ownership and autonomy, contributing directly to core product, infrastructure, and AI platform decisions while working closely with engineering and senior leadership in a highly collaborative, low-bureaucracy environment with direct access to decision-makers.
A genuine interest in investing, public markets, and fundamental business analysis is expected.
Bachelor's degree in Computer Science or equivalent practical experience
8+ years of experience designing, building, and maintaining software systems
Excellent backend expertise in at least one strongly typed language, preferably TypeScript
Solid understanding of cloud computing primitives, especially AWS
Strong understanding of agentic AI concepts such as tool use, function calling, state machines or graphs, retrieval and reranking, structured outputs, memory, guardrails, and evaluation
Experience developing and deploying agentic workflows using frameworks such as LangChain, Mastra, or LangGraph
Build end-to-end distributed agentic AI solutions that are reliable and scalable
Lead cross-functional initiatives requiring coordination across multiple teams and shared systems
Mentor other engineers and define quality standards and best practices
Own long-term maintainability, observability, and cost efficiency of AI systems
Monitor model quality drift, prompt alignment, alerting, and operational health
Prior experience leading an AI systems team
Experience shipping and operating multiple GenAI or LLM systems in production
Hands-on experience debugging scaled LLM systems and participating in incident response
Experience building human-in-the-loop evaluation pipelines
Experience with RAG, embeddings, and model fine-tuning
Experience implementing evaluation suites for agentic systems running in production
Hybrid — 4 days on-site in Prague, Czech Republic / 1 day remote.
