Engineering Excellence Engineer 2 in New York

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application

Datadog is seeking a highly motivated Senior Corporate Development Lead to drive our AI product strategy, build strong relationships across the founder and VC ecosystem, and support high-impact initiatives including acquisitions, venture investments, and startup partnerships. You will be part of a small, high-visibility team that reports directly to Datadog's Founder/CEO. The ideal candidate is passionate about AI and developer tools, comfortable rolling up their sleeves, and excited to operate in a fluid, technically demanding environment. You will support evaluations, source promising AI startups, collaborate closely with internal product and engineering leaders, and help position Datadog as the preferred partner for the next generation of founders. This role is ideal for someone who is hungry for increased responsibility, operates with authenticity and creativity, and prioritizes the company's interests. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Support Datadog's AI product strategy by analyzing emerging technologies, market opportunities, and competitive dynamics. Source high-potential AI startups for acquisition, investment, or partnership, and build a strong presence across the founder and VC ecosystem through meetups, conferences, and events. Drive workstreams across diligence, valuation, financial modeling, strategic assessment, and internal recommendations. Partner with Product and Engineering leaders to evaluate build/buy/partner opportunities aligned with Datadog's AI roadmap. Support negotiation processes, including term sheets and partnership structures, and collaborate on integration planning with cross-functional partners after deals close. Help attract early-stage AI companies into Datadog's startup program. Wh

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We are seeking a Senior Product Security Engineer to serve as a technical leader and strategic contributor within our Product Security team. This role goes beyond execution — you will drive the evolution of CLEAR’s application security posture by influencing architecture, shaping security engineering processes, and mentoring team members in security and engineering. You’ll lead security initiatives across the organization and help embed security into every stage of our software development lifecycle. What you'll do: Drive security strategy and implementation across all CLEAR products and engineering teams, ensuring consistent protection of customer and business-critical assets. Partner with engineering leadership to align application security initiatives with company-wide technology and product roadmaps, balancing innovation with risk mitigation. Provide technical leadership across CLEAR’s application security initiatives, guiding architecture, design, and development to meet high security standards. Serve as a trusted advisor to cross-functional teams — including Engineering, DevOps, Product, GRC, and IT — enabling secure-by-design practices across the organization. Design and drive implementation of scalable automated security controls and testing frameworks integrated into CLEAR’s CI/CD pipelines. Lead complex threat modeling, architecture reviews, and risk assessments across high-value systems and platforms, driving meaningful security outcomes. Engage with CLEAR's customers to provide insight and support their fraud and ident

Become a part of our caring community You have shipped AI products before. You understand the difference between a demo and a production system. You have strong opinions about evaluation frameworks because you have experienced the consequences of operating without them. You are at your best when you own architecture decisions while continuing to build and deliver critical code yourself. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to source documents, and route complex cases to human experts. The output of these systems supports healthcare decisions that impact real members. As a Lead AI Applied Engineer, you will provide technical leadership for AI-enabled products and platforms, define architectural direction, establish engineering standards, and personally design and build the most critical components of our systems. You will lead through both technical expertise and execution, helping the team deliver reliable, scalable, and auditable AI solutions in a highly regulated healthcare environment. Why Join Us Lead the architecture of production AI systems where LLMs are foundational to the product experience. Make key technical decisions regarding model selection, system boundaries, platform architecture, and build-versus-buy strategies. Own the highest-risk and highest-impact technical challenges involving reliability, explainability, and correctness. Influence engineering culture and establish standards that shape how the team builds and ships AI products. Work on systems operating at meaningful scale, processing millions of documents and supporting healthcare decisions across a large member population. Partner

Become a part of our caring community Every large organization is making critical decisions today about how it will leverage AI over the next decade. Few have leaders who can both define that vision and demonstrate its viability through hands-on engineering. This role requires both. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations to source documents, and route difficult cases to human experts. These capabilities support decisions that impact real healthcare outcomes for members. As a Principal AI Applied Engineer, you will define the technical strategy, architectural standards, and long-term vision for AI-enabled products across the organization. You will influence enterprise-wide decisions regarding AI platforms, model strategies, engineering standards, and technology investments while remaining deeply hands-on in prototyping, experimentation, architecture, and software development. This is the highest-level individual contributor role within the AI Applied Engineering organization. Success requires exceptional technical depth, organizational influence, strategic thinking, and the ability to translate emerging AI capabilities into scalable, reliable, and responsible production systems. Why Join Us Shape the long-term AI architecture and engineering direction for a large enterprise healthcare organization. Influence how AI-enabled products are designed, built, evaluated, deployed, and governed across multiple teams. Drive strategic decisions involving models, vendors, platforms, infrastructure, and shared capabilities. Prototype and validate emerging technologies before the organization invests at scale.</

Base — $160k – $180k | OTE — ~$230k – $255k | Equity — 0.3% | In-person NYC About Datalab Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right. We're at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, chandra, surya, marker, and lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face. Role Overview We're looking for a Founding Customer Success Manager to own the relationship with our enterprise customers after they sign. You'll be accountable for adoption, retention, and growth — making sure customers get real value from our models, stay for the long run, and expand their usage over time. You'll be the face of Datalab for every account you own: their trusted advisor, their first call when something matters, and the person keeping their goals moving forward. You will be the commercial and relationship manager who owns the account strategy after a deal has been signed. You'll orchestrate the right people internally so the customer always feels progress. You'll know the product and the customer's architecture well enough to lead most conversations yourself, and you'll pull in Engineering when an account needs it. We also have a long tail of self-serve customers using our API. Many are strong candidates to expand into enterprise contracts, and you'll own that self-serve → enterprise motion end to end — from spotting high-potential accounts to closing the upgraded contract. This role is ideal for someone who thrives at the intersection of c

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The FinOps function is responsible for financial accountability, visibility, and optimization across all engineering-related spend at Plaid. This includes cloud infrastructure, AI/ML and data workloads, third-party SaaS tools, and other technical investments that support Plaid’s products and internal platforms. The team operates at the intersection of Engineering, Product, and Finance, ensuring that spending decisions are transparent, intentional, and aligned with product strategy and business priorities. Rather than functioning as a cost-control or approval layer, FinOps enables teams to understand, own, and optimize their spend while maintaining engineering velocity. Responsibilities Monitors and analyzes engineering spend across cloud, AI/ML, data platforms, and SaaS, identifying trends, anomalies, and optimization opportunities. Builds and maintains forecasts for engineering spend, partnering with Finance and engineering leaders to understand drivers, assumptions, and risks. Partners with engineering, product, and TPMs to incorporate cost considerations into roadmaps, architectural decisions, and execution plans. Leads cost optimization initiatives, such as rightsizing, commitment strategies, an

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. The Customer Growth & Experience (CGX) team owns the full customer lifecycle - from the moment a customer lands on plaid.com to their journey across onboarding, activation, adoption, and long-term success. Within CGX, the Growth team owns Plaid's highest-leverage revenue levers. We optimize the self-serve funnel from a customer's first onboarding step through go-live and scale, build the upsell motion that expands existing customers, partner with GTM to remove friction from the sales flow, and own the premium enterprise features that unlock our largest customers. We operate data-first, using funnel analytics and experimentation to find and prioritize the bets that move the business. As a Product Manager on the Growth team, you'll own one of Plaid's highest-leverage revenue surfaces: the self-serve funnel that takes customers from their first onboarding step through go-live and scale. You'll work to increase acquisition, reduce friction, and improve revenue efficiency across the SMB and long-tail base. You'll partner closely with the Web team, Engineering, Design, BI/DS, Marketing, and Sales to build the upsell motion that expands existing customers, whether served in-product or routed to GTM as

This is a senior individual contributor role for someone who wants to actively shape how Engineering, one of the most important parts of how Datadog develops its people. You'll sit at the center of Datadog's biggest talent bets for Engineering: how we build leaders, define career paths and org design, evolve performance, move talent internally, and plan succession for our most critical roles. You’ll own this work end to end, from the first framing conversation with senior leaders through to delivering a program running at scale. AI is changing how Engineering builds software, and it is changing how People builds the programs that support Engineering too. This role sits at the centre of both: understanding how AI is reshaping engineering roles, skills and structures, and building AI-powered solutions within People to keep pace. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Design and lead complex talent programmes for Engineering, spanning leadership capability, career architecture, org design, performance, internal mobility and succession for critical roles. Partner directly with PBPs and senior leaders to turn ambiguous problems into clear programme goals, design principles and success measures. Help Engineering and People understand and respond to how AI is reshaping roles, skills and ways of working, and translate that shift into practical talent and org design choices. Stay hands-on from concept through to adoption: this is a build and run role, not a strategy and handover role. Work across Enablement, Learning, People Analytics and People Systems so what you build scales and embeds into core people processes. Equip PBPs with frameworks, tools and executive-ready narratives that support real adoption in the business. Operate in ambigu

As a Staff Product Manager on Datadog's Observability Data Platform (ODP) , you will lead product management for a portfolio of foundational platform bets — work that changes the cost structure and capability of the platform itself, not the cost of any single feature. Among ODP’s portfolio of engineering work are efforts to bring the platform's unit cost down meaningfully each quarter, plus a slate of architectural bets aimed at order-of-magnitude cost reduction over the longer horizon. The work you'll lead reshapes how Datadog ingests, routes, and exposes telemetry value to customers — and is foundational to how every product team in Datadog's ecosystem will think about telemetry economics going forward. This role reports to the Group Product Manager of ODP. What You'll Do: Set product direction across foundational platform bets by defining problems and desired outcomes, partnering with engineering to determine slices of work that drive value in phases for users and the business. Collaborate on the long-term cost-and-value architecture of the platform — how value-aware telemetry, innovative data engines, and customer-facing cost stories fit together over multiple quarters. Develop and defend sizing and impact estimates for large, diffuse programs — credibly produce the analysis that engineering leadership and pricing partners need to make resourcing and prioritization calls. Anticipate and communicate market trends in telemetry economics and agentic observability and how they shape platform investment. Develop deep understanding of cost-to-serve by partnering with engineering on the unit economics of the data platform and bring that cost-profile understanding into collaborative discussions with product verticals about customer-facing trade-offs. Surface the customer-positive angles in cost work that engineering-led optimization tickets don't currently make visible. Deliver concise written and verbal communication to executive, engineering, and customer audien

Become a part of our caring community Help shape practical, responsible AI solutions that improve healthcare experiences and outcomes. Humana’s Enterprise AI organization develops safe, scalable AI solutions across our Insurance and CenterWell businesses. We bring together product managers, data scientists, engineers, policy experts, and business leaders to apply emerging technology to meaningful healthcare challenges. As Associate Director of Applied AI, you will lead teams that design, build, and deploy enterprise AI solutions, with a focus on generative AI and intelligent agents. You will connect technical strategy to business needs, guide responsible delivery in a regulated environment, and help teams turn promising ideas into measurable outcomes for members, patients, and associates. Key Responsibilities Lead and mentor teams developing production-ready AI solutions that improve healthcare delivery, member experiences, and business operations. Help define and execute the roadmap for applied AI initiatives in alignment with enterprise priorities and business needs. Guide the evaluation and adoption of machine learning, generative AI, large language models, multimodal models, and intelligent agent technologies. Oversee scalable APIs, frameworks, data pipelines, retrieval-augmented generation solutions, and agent orchestration capabilities. Partner with product, data science, engineering, architecture, security, and business teams to translate requirements into reliable solutions. Establish standards for AI evaluation, obse

As a Cloud Security Engineer you will partner with different stakeholders across the organization to secure our cloud infrastructure. As part of the Platform Security organization we secure the building blocks of Datadog’s applications and infrastructure. We do this by building solutions to solve systemic risks and combine an approach of making the secure path easier and the insecure path harder to secure and accelerate the business. We regularly partner with the most bleeding edge internal products and are working to solve and build solutions to enable our safe usage of AI. We also develop AI based solutions to enable security at scale. We are looking for a Service Mesh and Kubernetes focused security specialist to help round out an incredibly strong infrastructure security focused group. You will rotate through a variety of internal projects and gain deep exposure to Datadog’s infrastructure. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Solve our most challenging cloud infrastructure security problems starting with our core building blocks and golden paths. Enable our engineers to build and ship secure solutions quickly. Build and extend Datadog’s Platform Security solutions. Leverage and influence the direction of Datadog’s products to secure our infrastructure, and provide internal feedback that enables our teams to improve the products for ourselves and our customers. Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent professional experience. Passionate about advocating for and implementing solutions to complex problems, at-scale, in a large multi-cloud environment. You don’t want to just provide security recommendations, you want to help imple

Datadog's Software Engineers with Systems depth leverage their experience with systems and tooling to build software that ensures Datadog remains reliable, performant, and secure. For this track, their Software Engineering experience may resemble the Distributed Systems track, but is typically applied in combination with their systems experience to build and run internal platforms and tools that our products are built on. These people typically have deep experience building and managing large cloud infrastructure deployments, or leading reliability efforts for orgs similar to ours, or building release machinery to allow hundreds or thousands of devs to do their jobs without stepping on each others' toes. The systems and tooling where they may have experience depth may include (but not limited to): bazel, build tooling, cassandra, CDN, chef, configuration management, container orchestration, consul, docker, elasticsearch envoy, haproxy, kafka, kubernetes, load balancing, network architecture, postgres, redis, release management, RPC frameworks, service discovery, spinnaker, terraform, zookeeper. Bonus: You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how This job is available in various departments within our company; to conform to US export control regulations, some of these roles may require candidates to be eligible for any required authorizations from the US government. #LI-KM5 Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan. Th

ABOUT PROPRIETARY RESEARCH On our proprietary research team—Market Intelligence— you will uncover insights about markets and the broader economy through deep compliant fundamental research and applying data science and engineering techniques to alternative data sets. In partnership with our investment professionals and Compliance team, our team of analysts, data scientists and engineers work together to produce compliant research and build tools that inform our firm’s investments. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. WHAT YOU’LL DO As a Macro Analyst, Market Intelligence covering the US, you will work with alternative data to gather macroeconomic context and identify insights relevant to rates and FX markets. You will then partner with our team of data scientists and engineers to develop analyses that you deliver as synthesized insights to our investment professionals to help aid in their research processes. The work is ever evolving, affording opportunities to tackle new challenges alongside research teammates from diverse backgrounds. Specifically, you will: Analyze and interpret alternative data from multiple sources and develop subject-matter expertise on the key themes and KPIs that drive the markets within your assigned coverage Produce research for internal consumption by our investment professionals across a variety of channels, including written reports, verbal communication, data feeds, and visualizations Interact directly with our investment professionals to learn the macro investment process from them and help drive more informed investment decisions Collaborate with our proprietary research teams including Data Sourcing, Data Science, and Data Engineering, as well as Compliance, to source, evaluate, and draw value from new and existing data assets to produce actionable research for investment professionals WHAT’S REQUIRED &nb