Manager I, Engineering - Applied AI - Natural Language & Conversational Interfaces

The shape of it

In the posting’s own words

Applied AI is where Datadog's ambitious AI bets get built and shipped ( Bits Chat , updog ). We sit at the intersection of research and product: turning promising capabilities from Datadog AI Research lab and the research community into production systems that reach real customers. The team builds the foundations for agentic systems capable of operating at scale in complex production environments. Current bets span agents that run autonomously at scale, context and memory layers that make those agents more intelligent over time, and tools that help customers build and validate AI-native services in production. The mandate is to move fast from idea to customer impact, and when a product finds its footing, to set it up for growth. As an Engineering Manager I in Applied AI, you will lead a team of engineers and applied scientists working on one of these challenges. You will define technical direction, run short feedback loops, make deliberate decisions about what to pursue or stop, and work closely with product managers, research teams, and cross-functional partners to ship AI capabilities that matter. At Datadog, we place value in our office culture, the relationships and collaboration it builds and the creativity it brings. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do

What it asks for · 12

• A people-focused manager with experience leading and mentoring engineers, able to develop strong engineering talent in a fast-moving domain
• A technical leader with deep expertise in one or more areas of AI or machine learning: large language models, retrieval-augmented generation (RAG), semantic search, agentic systems, deep learning, or NLP
• Well-versed in evaluation methodologies for AI systems, both offline benchmarks and online metrics
• A strong product instinct: able to anchor early-stage work in concrete customer problems, define success criteria before writing code, and actively contribute to shaping product direction alongside product and research partners
• Experience taking AI products from 0 to 1 is strongly valued: able to bring structure to early-stage work by scoping clear hypotheses, moving quickly toward signal, and making deliberate decisions about what to pursue, pivot, or stop
• BS/MS/PhD in Machine Learning, Computer Science, Engineering, or related field, or equivalent professional experience
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture with the ability to join Community Guilds (Datadog employee resource groups)
• Free, global Spring Health benefits for employees and dependents age 6+
• Competitive global benefits
• Giving programs

Degree language

• BS/MS/PhD in Machine Learning, Computer Science, Engineering, or related field, or equivalent professional experience

Tools and skills named

Words the posting leans on

• product10×
• research7×
• systems7×
• benefits6×
• applied4×
• customer4×
• engineers4×
• experience4×
• growth4×
• learning4×
• manager4×
• quality4×
• agents3×
• bets3×
• builds3×
• culture3×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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