About Sovrn

Every interesting company solves important problems for other people.  Sovrn is a Software and Data business that helps Open Web businesses be and remain independent.  We help them understand their business better, operate more efficiently, and make & keep more money.

• We believe in the freedom and free-flow of information.
• We believe the Open Web is the largest source of this information.
• We believe in helping Open Web businesses be and remain Independent.

Through Software products and Data solutions we help our customers:

• Understand their business better, so they can make better decisions
• Operate their business more efficiently, so they can invest in what matters most
• Make (and Keep) more money, so they control their own destiny

About the Role

We're looking for a Principal Software Engineer with deep roots in adtech infrastructure and a genuine conviction about what AI-native engineering looks like in practice. This role is backend-focused at its core — you'll work on the systems that power our exchange, from bid request processing and traffic shaping to data pipelines and auction logic. But we're also at an inflection point in how we build software, and we want this person to help lead us through it.

From a generative/agentic AI capabilities standpoint, we already use LLMs and agentic tooling across our data stack and, we’re looking for is someone who can help us take that from general adoption to intentional practice — who has strong opinions about where AI creates real leverage in a high-throughput adtech environment, and who can bring the rest of the engineering organization along with them.

Languages/components/tools in our stack: Java, Kafka (Redpanda), AWS, Databricks, Datadog, ONYX.

What you'll be doing:

• Own the design and evolution of backend systems that operate at exchange scale — high throughput, low latency, always on
• Lead architectural decisions across auction infrastructure, bid processing, traffic shaping, and supply-side integrations
• Establish and champion AI engineering practices across the team — from prompt engineering and RAG patterns to agentic workflow design and LLM evaluation
• Identify high-leverage opportunities to apply AI in our adtech stack: traffic scoring and filtering, bid shading, yield optimization, anomaly detection, and automated decisioning
• Set standards for how we evaluate, trust, and operate AI-powered systems in production — including observability, fallback behavior, and model governance
• Drive technical standards, design reviews, and engineering best practices across a senior team
• Partner with product, data science, and platform teams to ship end-to-end
• Help the broader engineering team build fluency and confidence with AI tooling, not just tolerance of it
• Mentor and level up engineers through code review, design collaboration, and hands-on guidance

A successful candidate will have:

• 10+ years of software engineering experience, with a strong backend track record
• 5+ years working specifically in adtech infrastructure — SSP, DSP, exchange, or ad server environments
• Deep fluency in the programmatic ecosystem: OpenRTB, bid request/response flows, auction mechanics, supply path optimization, or similar
• Experience building and operating systems at exchange scale — high QPS, strict latency budgets, fault tolerance
• Demonstrated experience leading AI or agentic engineering efforts in production environments — not just experimentation, but shipped, operated, and iterated on
• Hands-on experience with LLM integration patterns: RAG, tool use, multi-step agentic workflows, prompt engineering, and evaluation frameworks
• Strong distributed systems fundamentals: messaging, caching, service architecture, observability
• Comfort driving technical decisions in ambiguous, fast-moving environments
• A point of view on where AI is and isn't the right tool — and the credibility to make that case

Location: This position is based in our Boulder Colorado or New York City office. Applicants need to be able to commute/travel to our Boulder or New York City location. For exceptional candidates we would consider remote locations in these states: AZ, CA, CO, GA, MD, MA, MI, MO, NJ, NY, NC, OK, TX, UT, WA. #LI-Hybrid #LI-Remote

We understand that no candidate is perfectly qualified for any job. Experience comes in different forms; many skills are transferable; and passion goes a long way. Even more important than your resume is a clear demonstration of accountability and the ability to thrive in a fluid and collaborative environment. We expect you to learn new things in this role and encourage you to apply if your experience is close to what we’re looking for.

Sovrn Core Values: Candid, Customer Empathy, Learning, Scrappy, Second Order Thinking

Compensation and Benefits

The base pay range for this position is $200,000 to $240,000 annually. In addition to the base salary, the total compensation package includes bonus, equity, and benefits. Actual earnings may vary depending on the candidate’s direct experience, skills, industry knowledge, and location.

Sovrn offers a full slate of benefits from competitive salaries, stock options, medical, dental, and vision coverage, short and long-term disability, life insurance, 11 paid holidays, flexible vacation, commuter benefits, a 401(k) plan and match, and a paid parental leave program.

Job Posting

Applications will be accepted until July 1, 2026.

Equal Opportunity Employer

Sovrn is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, color, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristic protected by law.

Recruitment Agencies

Sovrn does not accept agency resumes. Please do not forward resumes to our jobs alias or Sovrn employees. Sovrn is not responsible for any fees related to unsolicited resumes.

About Sovrn

Every interesting company solves important problems for other people.  Sovrn is a Software and Data business that helps Open Web businesses be and remain independent.  We help them understand their business better, operate more efficiently, and make & keep more money.

• We believe in the freedom and free-flow of information.
• We believe the Open Web is the largest source of this information.
• We believe in helping Open Web businesses be and remain Independent.

Through Software products and Data solutions we help our customers:

• Understand their business better, so they can make better decisions
• Operate their business more efficiently, so they can invest in what matters most
• Make (and Keep) more money, so they control their own destiny

About the Role

We’re looking for a Principal Software Engineer (Data) with deep roots in adtech data infrastructure and a genuine conviction about what AI-native data engineering looks like in practice. This is a specialized principal-level engineering role — one that carries all the architectural ownership and technical leadership expectations of a Principal Software Engineer, focused on Sovrn’s Data Collective.

From a generative/agentic AI capabilities standpoint, we already use LLMs and agentic tooling across our data stack and, we’re looking for is someone who can help us take that from general adoption to intentional practice — who has strong opinions about where AI creates real leverage in a high-throughput adtech environment, and who can bring the rest of the engineering organization along with them.

Languages/components/tools in our stack: Python, Pyspark, Kafka, Databricks, AWS

What you'll be doing:

Data Platform & Architecture

• Own the design and evolution of data platform systems that operate at exchange scale; high throughput, real-time streaming, and always-on batch pipelines
• Lead architectural decisions across data infrastructure: pipeline design, data modeling, lakehouse architecture, and data services layers
• Specify data platform components and configurations required for pipeline implementation; define pipeline observability to understand and improve performance at massive scale
• Research, implement, and evolve methods to process and democratize data across the organization
• Drive technical standards, design reviews, and engineering best practices across a senior team
• Partner with product, data science, and platform teams to ship end-to-end

AI & Agentic Engineering Leadership

• Establish and champion AI engineering practices across the team, from prompt engineering and RAG patterns to agentic workflow design, LLM evaluation, and progressive implementation of agentic design patterns
• Identify high-leverage opportunities to apply AI in our data stack: intelligent pipeline optimization, anomaly detection, automated data quality, forecasting, and LLM-powered data services
• Lead the evolution of our existing LLM and agentic tooling from passive use to intentional, well-architected integration within our data platform
• Set standards for how we evaluate, trust, and operate AI-powered systems in production, including observability, fallback behavior, and model governance
• Help the broader engineering team build fluency and confidence with AI tooling, not just tolerance of it

Collaboration & Mentorship

• Provide domain expertise across the organization to enable business growth through data services and data models
• Provide counsel to all consumers and stakeholders of data to enable efficient and impactful use of our data assets
• Mentor and level up engineers through code review, design collaboration, and hands-on guidance; foster a culture of innovation and continuous learning
• Operate with high autonomy across ambiguous, high-impact problems

A successful candidate will have:

• 10+ years of software engineering experience, with a strong data engineering and backend track record
• 5+ years working specifically in adtech data infrastructure, SSP, DSP, exchange, or ad server environments
• Deep fluency in the programmatic ecosystem: OpenRTB, bid request/response flows, auction mechanics, supply path optimization, or similar
• Excellent understanding of real-time streaming and batch pipelines, big data, and data lakes; hands-on experience in distributed data processing in the AWS ecosystem
• Strong understanding of second-layer big data platforms such as Snowflake and Databricks, applicable use cases, best practices, implementation, and support considerations
• Strong experience in structured, unstructured, and semi-structured data techniques; metadata management, data lineage, and data governance
• Experience with data security and compliance (PII, CCPA, GDPR, etc.)
• Demonstrated experience leading AI or agentic engineering efforts in production environments; not just experimentation, but shipped, operated, and iterated on
• Hands-on experience with LLM integration patterns: RAG, vector DBs, tool use, multi-step agentic workflows, prompt engineering, and evaluation frameworks
• Ability to clearly document and communicate architectural concepts at multiple levels; ability to lead problem definition, solution designs, and implementation work plans
• Understanding of DevOps and SRE practices
• Comfort driving technical decisions in ambiguous, fast-moving environments
• A point of view on where AI is and isn’t the right too, and the credibility to make that case

Location: This position is based in our Boulder Colorado or New York City office. Applicants need to be able to commute/travel to our Boulder or New York City location. For exceptional candidates we would consider remote locations in these states: AZ, CA, CO, GA, MD, MA, MI, MO, NJ, NY, NC, OK, TX, UT, WA. #LI-Remote, #LI-Hybrid

We understand that no candidate is perfectly qualified for any job. Experience comes in different forms; many skills are transferable; and passion goes a long way. Even more important than your resume is a clear demonstration of accountability and the ability to thrive in a fluid and collaborative environment. We expect you to learn new things in this role and encourage you to apply if your experience is close to what we’re looking for.

Sovrn Core Values: Candid, Customer Empathy, Learning, Scrappy, Second Order Thinking

Compensation and Benefits

The base pay range for this position is $200,000 to $240,000 annually. In addition to the base salary, the total compensation package includes bonus, equity, and benefits. Actual earnings may vary depending on the candidate’s direct experience, skills, industry knowledge, and location.

Sovrn offers a full slate of benefits from competitive salaries, stock options, medical, dental, and vision coverage, short and long-term disability, life insurance, 11 paid holidays, flexible vacation, commuter benefits, a 401(k) plan and match, and a paid parental leave program.

Job Posting

Applications will be accepted until July 1, 2026.

Equal Opportunity Employer

Sovrn is proud to be an Equal Opportunity Employer and provides equal employment opportunities to all employees and applicants regardless of race, color, religion, gender, gender identity, age, national origin, disability, parental or pregnancy status, marriage and civil partnership, sexual orientation, veteran status, or any other characteristic protected by law.

Recruitment Agencies

Sovrn does not accept agency resumes. Please do not forward resumes to our jobs alias or Sovrn employees. Sovrn is not responsible for any fees related to unsolicited resumes.

The Product Solutions Architecture (PSA) team acts as a technical multiplier across Datadog. PSAs are domain experts who partner with Field teams on complex customer use cases across pre- and post-sales engagements and scale their impact by producing reusable collateral, including reference architectures, technical guides, and enablement assets. By feeding real-world customer insights back to Datadog Product teams, PSAs help influence product roadmaps while accelerating adoption, usage, and long-term customer success.

Datadog’s LLM Observability product enables organizations to monitor, troubleshoot, and optimize large-scale LLM-powered applications with confidence, while meeting requirements around data privacy, compliance, and cost management. As a Product Solutions Architect, you will partner closely with Datadog customers and the LLM Observability product team to design architectures, implement best practices, and drive adoption of LLM observability across customer environments.

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:

• Serve as the in-house subject matter expert for Datadog’s LLM Observability product
• Partner with Field teams to provide hands-on technical and architectural guidance to enterprise customers adopting LLM Observability
• Create high-impact technical collateral, including reference architectures, technical guides, cookbooks, and documentation to enable Field teams and the broader customer community
• Build proofs of concept and small-scale deployments to validate solutions and reproduce real-world customer environments
• Act as a trusted advisor to Product Management by delivering actionable feedback informed by real-world field experience

Who You Are: 

• You bring a strong software engineering foundation, with hands-on experience building and operating LLM-powered applications in production environments, and are comfortable diving deep into codebases to understand architectural decisions, tradeoffs, and implementation details
• You are familiar with distributed systems and core observability concepts, such as tracing, metrics, and logging, and can translate those patterns into the emerging LLM observability domain, including LLM spans, evaluations, and prompt templates
• You have experience with languages such as Python and/or JavaScript/TypeScript
• You are comfortable operating in rapidly evolving, ambiguous technical domains
• You build deep context across teams and translate it into reusable, scalable solutions
• You take ownership from problem definition through implementation and measurable outcomes
• You are highly detail-oriented, particularly when working on architectures and customer-facing technical assets
• You bring strong listening and consultative skills and are experienced supporting customers in high-pressure, complex situations
• Able to sit up to 4 hours, traveling to and from client sites 
• Able to travel via auto, train, or air up to 40% of the time 

Bonus Points:

• Successful track record with 5+ years experience working as an Architect or Consultant 
• Experience using Datadog and/or other observability tools in an SRE or DevOps capacity
• Experience with LLM application evaluation and testing frameworks

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth: 

• Best-in-breed onboarding
• Generous global benefits
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, able to join our Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.