Hi, we're Oscar. We're hiring an Applied AI Engineer to join our AI team.

Oscar is the first health insurance company built around a full stack technology platform and a focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role

Join Oscar’s AI team to build and launch transformative AI-powered products that redefine the healthcare experience for millions. As an Applied AI Engineer, you’ll take end-to-end ownership of high-impact projects—conceiving, prototyping, and deploying generative AI solutions that solve real-world problems across the healthcare ecosystem.You’ll work alongside a world-class team of engineers and data scientists, rapidly iterating on ideas and shipping production-ready applications that drive measurable business and user outcomes. You’ll have the autonomy to identify opportunities, experiment with the latest AI models and techniques, and deliver solutions that streamline operations, improve patient experiences, and move the needle for Oscar and our members.

You will report to the Sr. Director, AI.

Work Location: This position is based in our New York City office, requiring a hybrid work schedule with 3 days of in-office work per week. Thursdays are a required in-office day for team meetings and events, while your other two office days are flexible to suit your schedule. #LI-Hybrid

Pay Transparency: The base pay for this role is: $163,944 - $236,911 per year. You are also eligible for employee benefits, participation in Oscar’s unlimited vacation program, company equity grants, and annual performance bonuses.

Responsibilities

• Lead the design, development, and deployment of AI-driven products and features, from zero-to-one prototypes to robust production systems.
• Collaborate cross-functionally with product, design, and business teams to deeply understand user needs and deliver solutions that move key metrics.
• Rapidly experiment with new models, techniques, and tools (including LLMs, RAG, and agentic workflows), iterating based on data and user feedback.
• Build and scale full-stack applications and intelligent agents that automate complex healthcare workflows and deliver seamless user experiences.
• Stay on the cutting edge of the AI ecosystem, evaluating and integrating emerging technologies to keep Oscar at the forefront of healthcare innovation.
• Contribute to Oscar’s AI strategy and technical vision, helping shape the future of healthcare through technology.
• Other duties as assigned

Qualifications

• 7+ years of professional experience in software engineering, data science, or a related field, with a track record of impactful accomplishments
• Strong Python programming skills
• Experience solving complex, ambiguous problems 
• Experience designing and analyzing experiments or evaluations
• Experience or an interest in prototyping full-stack applications

Bonus Points

• Experience with the healthcare industry. Familiarity with claims or clinical data.
• Degree in math, statistics, data science, or engineering.
• Our ideal candidate is a data scientist with an engineering background, an engineer with a data science background, or a founder-type who combines product thinking, rapid prototyping, and hands-on coding to deliver real-world impact.
• Experience with NLP, neural networks, transformers, and modern AI frameworks.
• Knowledge of containerization and deployment tools (e.g., Docker, Kubernetes) or full-stack development (e.g., React, Golang).
• Experimental mindset: comfort with testing hypotheses and iterating on failures.

About this role

We are looking for an experienced Senior Business Intelligence Analyst to scale a critically important function responsible for building and maintaining systems, processes and services that enable us to understand financial performance and unlock key business insights at Faire. The ideal candidate for this role will ensure key accounting procedures are automated in ways that are accurate, efficient, easy-to-understand, and scalable. This role will sit in the Finance department and collaborate with team members from a breadth of functional groups across Faire, including Accounting, Finance & Strategy, Engineering and Data Infrastructure. This role will have a tremendous impact on the ability for Faire employees to use data effectively in order to report numbers externally and make impactful decisions internally. As an early member of a burgeoning team, you will have the opportunity to write the roadmap for how we improve access to business critical data and unlock automation that amplifies the impact of a variety of functions. 

What you’ll do 

• Scope, design, create, and manage complex ETL flows that aggregate and synthesize key business performance metrics and financial reporting, ensuring efficient, accurate, and scalable data models using best practices 
• Act as a trusted analytical partner to the Accounting and Finance teams providing technical expertise, gathering requirements from product and operational teams, and enabling data-driven decision-making and accountability by ensuring core ledgers accurately reflect business changes 
• Collaborate closely with Engineering, Data Infrastructure, and other stakeholders as a key translator and process improver, gathering requirements and delivering impactful data solutions that ensure alignment and efficiency across the organization 
• Lead initiatives to drive data strategy, roadmap planning, and prioritization, ensuring alignment with business objectives 
• Act as a thought leader to expand the team’s influence and impact throughout the Finance team and the broader organization 
• Drive workflow automation and innovation across Finance, including identifying and implementing Gen-AI–enabled productivity solutions to modernize processes and increase team leverage

Qualifications

• 5+ years of work experience in Business Intelligence, Analytics Engineering, Data Analytics, or comparable function 
• Expert in SQL with focus on data modeling, large-scale data processing, and tool development for analytics or Financial use cases. 
• Experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms 
• Experience with analytics workflow tools (examples: Airflow, Docker, dbt), data warehousing and storage (examples: Snowflake, BigQuery, Redshift, S3), and data visualization tools (examples: Mode, Tableau, Looker) 

Nice to have: 

• Experience with Python, R or other programming languages 
• BA/BS degree, ideally in computer science, math or another quantitative field 
• Familiarity with version control using Git and proficiency in command-line tools for workflow automation and data manipulation

Salary Range

San Francisco and New York: The pay range for this role is $174,500 to $240,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank (the “Bank”) is seeking a VP-level AI/ML Engineer to deploy AI solutions at enterprise scale, with a strong emphasis on Large Language Model (LLM) applications and modern MLOps & AIOps practices. This role sits at the intersection of data science and software engineering, reporting to the manager of the IT Application Development and Support team and working closely with the Chief Artificial Intelligence Officer, transforming innovative AI prototypes into robust, scalable production systems. The AI/ML Engineer will lead the deployment of high-impact AI capabilities (e.g., generative AI systems, personalization engines, automation tools) and ensure scalable AI platforms that deliver real-world value. The role also includes designing, constructing, and maintaining the Bank’s AIOps solution, with Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Production Architecture & AIOps

• Establish and enforce architecture standards for production AI systems, including data pipelines, model serving infrastructure, and real-time inference services.
• Implement AIOps/MLOps pipelines for CI/CD of ML models, model governance, monitoring, and lifecycle management.
• Design and maintain scalable software applications with integrated AI/ML capabilities.
• Develop software architecture and design patterns to ensure performance and scalability.
• Write clean, maintainable code in general-purpose programming languages (Python, Java, C, C++, Go).
• Implement and manage data pipelines for preprocessing and transforming data for AI/ML models.
• Integrate AI/ML models into production environments and optimize for reliability and scalability.
• Apply Site Reliability Engineering (SRE) principles and implement monitoring and alerting solutions.
• Conduct code reviews and provide technical guidance to junior developers.
• Stay current with advancements in software engineering and AI/ML technologies.
• Adhere to agile and lean software development best practices.
• Thoroughly document all developed models and processes according to relevant policies and standards.
• Support the production environment by either resolving technical or functional issues, in line with the procedures defined by the Bank.

Cross-Functional Collaboration

• Partner with data scientists, AI scientists, product managers, data engineers, DevOps, and business stakeholders to operationalize AI algorithms.
• Mentor or train teams and coordinate between research-oriented AI scientists and engineering teams to continuously improve models with production feedback.

Scaling & Performance

• Ensure AI solutions perform at scale, handling thousands of daily inferences with low latency and high reliability.
• Optimize model serving using techniques like model compression, caching, and hardware acceleration.

Implement robust monitoring and alerting for model performance to detect and address degradation (e.g., drift, latency issues).

Qualifications & Skills:

• 6+ years of experience
• Master’s or PhD in a relevant field (Computer Science, Software Engineering,  Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML
• LLM & GenAI Mastery: Expert in building and deploying LLM-based applications using RAG, prompt engineering, and vector databases. Skilled in LLMOps tools (LangChain, LlamaIndex) and fine-tuning models for enterprise use, including agent-based architectures.
• MLOps & Cloud Infrastructure: Proficient in cloud ML platforms (AWS, GCP, Azure) and MLOps workflows. Uses Docker, Kubernetes, and IaC tools (Terraform, CloudFormation) for scalable deployments. Experienced in CI/CD, real-time inference, GPU optimization, and ML observability (Prometheus, Grafana, MLflow).
• Full-Stack Development: Capable of building end-to-end AI solutions, from front-end (React) to back-end APIs (Flask, FastAPI, Node.js). Skilled in integrating ML models with databases (SQL, NoSQL) and delivering seamless user experiences through robust software engineering.
• Proficient in Python (pandas, scikit-learn), deep learning (PyTorch/TensorFlow/Keras), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• Experienced with Snowflake-native ML (Snowpark Python, UDFs/UDTFs, Tasks/Streams).
• Competent in data engineering (SQL, ETL/pipelines, Spark/PySpark) and handling large structured/unstructured datasets.
• Strong understanding of AI/ML algorithms, application architecture, and design patterns.
• Excellent problem-solving, analytical, communication, and collaboration skills.

Preferred Qualifications & Skills

• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on experience with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions, and feature management/registry tooling.
• Familiarity with fairness toolkits, XAI frameworks, and preparing models for validation, audit, or regulatory exams.
• Knowledge of SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment.
• Excellent written and verbal communication skills.
• Strong listening and teaching abilities.
• Demonstrated analytical, troubleshooting, and problem-solving skills.
• Quick learner of new technologies.
• Self-directed with strong technology and communication skills.
• Ability to synthesize multiple sources of information and understand the broader operational context of the Bank.
• Collaborative team player with a practical and creative approach in a dynamic work environment.
• Ability to handle ambiguity, multitask, and adapt quickly to changing priorities.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Come Work With Us:

Metropolitan Commercial Bank (“MCB” or the “Bank”) is a New York City–based, full-service commercial bank providing tailored banking solutions to businesses, institutions, and individuals. Founded in 1999, MCB operates banking centers in Manhattan and Boro Park, Brooklyn, within New York City, as well as in Great Neck on Long Island, New York, and Lakewood, New Jersey. The Bank recently expanded to Miami, Florida with their newest Brickell banking center.

Metropolitan Commercial Bank offers a comprehensive suite of commercial, business, and personal banking products and services to small businesses, middle-market and corporate enterprises, private and public institutions, municipalities, and local government entities.

The Bank has earned national recognition for its financial performance, innovation, and strategic growth. The Bank was named one of Newsweek’s Best Regional Banks in 2024 and 2025. Additionally, MCB recently received Editor’s Choice recognition at the Banking Tech Awards USA for Digital Onboarding & Omnichannel Banking and in 2026, the Bank earned Great Place To Work certification and received the Web Award Standard of Excellence for MCBankNY.com.

We are a client-focused organization that values technological innovation and excellence. A strong technical mindset, AI fluency, and adaptive skills are essential for our employees to effectively contribute to our mission and drive our success. We foster human–AI teaming and strong governance to ensure technology is used responsibly and in alignment with Bank policies and procedures. For more information about the Bank, please visit the Bank’s website at MCBankNY.com.

Position Summary:

Metropolitan Commercial Bank is seeking a VP-level Applied AI & Machine Learning Scientist to design, build, and validate production-grade AI/ML and Generative AI solutions in a highly regulated banking environment. This role focuses on high-impact use cases—fraud detection, AML alert optimization, AI-assisted credit memo generation for underwriting decision support, contact center AI assistant/copilots, and personalization for treasury/commercial clients—delivered with rigorous governance, explainability, fairness testing, privacy-by-design, cybersecurity, and model lifecycle controls aligned to SR 11-7 and MCB’s Trustworthy & Responsible AI Principles. The role emphasizes Snowflake as the primary ML platform (e.g., Snowpark Python, UDFs/UDTFs, Tasks/Streams, and Snowflake-native ML).

Standard 4-day in-office requirement, 1 day remote (of your choosing)

Essential Functions & Responsibilities 

Applied AI/ML development:

• Design and implement models for fraud detection, AML alert scoring/triage, AI-generated credit memo drafting and underwriting decision support, contact center AI assistants, and personalization for commercial/treasury use cases.
• Leverage modern methods: Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings and vector databases, transformers, boosting, anomaly/outlier detection, and classical ML.
• Embed explainability (e.g., SHAP, interpretable scorecards/monotonic models) and conduct pre-/post-deployment bias testing with documented remediation.

Model validation, documentation & governance (SR 11‑7):

• Produce audit-ready documentation (methodology, assumptions, data lineage, limitations, testing) and register models in the inventory with owners/materiality.
• Facilitate independent validation/effective challenge; obtain required approvals before deployment; maintain change management and periodic review cadence.
• Define monitoring, drift thresholds, retraining triggers, and safe rollback/kill-switch procedures; maintain human-in-the-loop checkpoints for high-impact decisions.

Productionization & MLOps on Snowflake

• Package, deploy, and operate models via CI/CD, containerization, and model registry; instrument KPIs/KRIs and alerting dashboards. Operate models natively on Snowflake using Snowpark Python, UDFs/UDTFs, Tasks/Streams, and secure external access where required.
• Partner with Engineering to integrate models via secure APIs/batch; ensure scalability, resiliency, and observability in cloud/on‑prem (e.g., Snowflake, Azure ML, Databricks).

Regulatory, privacy, and cybersecurity alignment:

• Design for ECOA/Reg B (adverse action specificity), UDAAP, FCRA, GLBA privacy, and NYDFS 23 NYCRR 500 cybersecurity requirements.
• Apply privacy-by-design (data minimization, purpose limitation, retention), strong access controls/segregation, and secure SDLC/red teaming for GenAI stacks.

Third‑party AI & data stewardship:

• Support due diligence, testing, and ongoing monitoring of vendor AI/data providers per SR 23‑4; evaluate conceptual soundness, fairness, and security.
• Negotiate/verify contractual controls (no vendor training on MCB/NPI, subprocessors disclosure, audit rights, exit/portability).
• Ensure AEDT compliance (NYC Local Law 144) for any HR-related AI tools.

Cross‑functional partnership:

• Collaborate with Model Risk, Compliance/Legal, Cyber/IT, Data Privacy, Internal Audit, and business owners to meet objectives while staying within risk appetite.
• Communicate complex results, risks, and limitations clearly to technical and non‑technical stakeholders (management committees, examiners).

Innovation, coaching, and best practices:

• Evaluate emerging ML/GenAI methods, LLM evaluation techniques, Snowflake‑native capabilities (e.g., vector search, orchestration), and governance tooling; lead POCs within established control gates.
• Mentor junior staff; promote responsible AI practices, documentation standards, and reproducibility.

Qualifications & Skills:

• 6+ years of relevant work experience.
• Expertise in Python (pandas, scikit‑learn), deep learning (PyTorch/TensorFlow), NLP/LLMs, LangChain, embeddings/vector search, and classic ML.
• MLOps proficiency with CI/CD, containerization (Docker), registries, and observability; cloud ML (Snowflakes-native ML, Azure ML or Databricks preferred).
• Snowflake‑native ML proficiency: Snowpark Python, UDFs/UDTFs, Tasks/Streams; ability to build and operate ML workflows inside Snowflake.
• Data engineering competency (SQL, ETL/pipelines, Spark/PySpark); ability to work with structured/unstructured data.
• Explainability (e.g., SHAP) and fairness testing; ability to produce interpretable reason codes for ECOA/Reg B adverse actions as applicable.
• Strong grasp of SR 11‑7 lifecycle, model documentation, and operational monitoring within three lines of defense governance.
• Excellent communication; ability to translate technical detail to business/risk stakeholders and drive decisions.
• Curiosity and problem‑solving mindset; ability to balance innovation with disciplined risk management.

Preferred Qualifications & Skills

• Master’s or PhD in a relevant field (Computer Science, Machine Learning, Data Science, Statistics, etc.) is strongly preferred, especially with research or thesis work related to AI/ML, NLP, or model interpretability.
• Financial services domain experience (fraud risk, AML, underwriting, or commercial/treasury analytics).
• Hands-on with Snowflake ML/Snowpark (Python), Tasks/Streams, secure external functions; experience with feature management/registry tooling a plus. model registry and pipeline orchestration; Kubernetes a plus.
• RAG architectures, vector databases, prompt engineering, and LLM evaluation (accuracy, hallucination, safety).
• Fairness toolkits and XAI frameworks; experience preparing models for validation, audit, or regulatory exam discussions.
• Familiarity with SR 23‑4 (third‑party risk), NYC Local Law 144 (AEDT), NYDFS Part 500 (cyber).
• Ability to work in a constantly evolving environment
• Must have excellent written and verbal communication skills
• Must be a good listener and good teacher
• Demonstrate analytical, troubleshooting and problem-solving skills
• The ability to learn new technologies quickly
• Self-directed individual with technology and communication skills.
• Ability to take in multiple sources of information with an understanding of the bigger picture need, want, and operation of the Bank.
• Collaborative team-player who can find creative and practical solutions in a dynamic work environment.
• Ability to handle ambiguity, juggle multiple matters at once, and quickly and seamlessly shift from one situation or task to another.

Potential Salary: $130,000 - $200,000 annually

This salary range reflects base wages and does not include benefits, bonus, or incentive pay. Salary bands are purposefully wide ranging to encompass the different factors considered in determining where a candidate falls in the range, including but not limited to, seniority, performance, experience, education, and any other legitimate, non-discriminatory factor permitted by law. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed here.

Metropolitan Commercial Bank provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

This applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments.

The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.

You will:

• Build and maintain fault-tolerant, high-performance systems for serving LLMs workloads at scale.
• Build an internal platform to empower LLM capability discovery.
• Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
• Conduct architecture and design reviews to uphold best practices in system design and scalability.
• Develop monitoring and observability solutions to ensure system health and performance.
• Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment. 

Ideally you'd have:

• 5+ years of experience building large-scale, high-performance backend systems.
• Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
• Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
• Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
• Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
• Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
• Proven ability to solve complex problems and work independently in fast-moving environments.

Nice to haves:

• Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human evaluation and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition.

At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI.

At the foundation of these products is the Platform Engineering team. As a Staff Software Engineer, you will define and drive both the architectural roadmap and implementation of core platforms and software systems. You will be responsible for providing high-level vision and driving adoption across the engineering org for orchestration, data abstraction, data pipelines, identity & access management, and underlying cloud infrastructure.  You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

Impact and Responsibilities:

• Architectural Vision: You will drive the design and implementation of foundational systems, acting as a bridge between high-level business goals and technical goals.
• Cross-Functional Leadership: You will collaborate with cross-functional teams to define and drive adoption of the next generation of features for our AI data infrastructure.
• Technical Ownership: You are responsible for proactively identifying and driving opportunities for organizational growth, driving improvements in programming practices, and upgrading the tools that define our development lifecycle.
• Technical Mentorship: You will serve as a subject matter expert, presenting technical information to stakeholders and providing the guidance to elevate the engineering culture across the company.

Ideally you’d have:

• 8+ years of full-time engineering experience, post-graduation with specialities in back-end systems.
• Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS preferred).
• Demonstrated a track record of independent ownership and leadership across successful multi-team engineering projects
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc.
• Experience with orchestration platforms, such as Temporal and AWS Step Functions.
• Experience with NoSQL document databases (MongoDB) and structured databases (Postgres).
• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI, ArgoCD).

Nice to haves:

• Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt).
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:

• Create multi-layered guardrails around agents
• Optimize data retrieval for agents
• Orchestrate fleets of asynchronous agents
• Automatically alerts users to deviations in data
• Illustrating how an agent reached a decision

As a Senior Software Engineer, you will lead the development of a vertical feature or a horizontal capability to include defining requirements with stakeholders and implementation until it is accepted by the stakeholders.

You will: Lead the design and implementation of scalable backend systems and distributed architectures for Federal customers.

• Manage the full lifecycle of feature development from requirement definition to deployment on classified networks.
• Direct the orchestration of asynchronous agent fleets to meet mission requirements.
• Lead customer engagements to translate mission needs into technical requirements.
• Own the communication with stakeholders to ensure implementation meets defined acceptance criteria.
• Conduct technical reviews and identify risks within machine learning infrastructure and model serving.
• Drive the platform roadmap by providing technical specifications for Federal product offerings.

Ideally you will have: 

• Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We are looking for a Mission Software Engineering Manager to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.  

You will:

• Recruit a high-performing engineering team. 
• Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of engineers working on Generative AI projects. 
• Collaborating with cross-functional teams to define, design, and execute strategic roadmap.
• Work directly with customers to understand their problems and translate those into features in Scale’s platform.
• Be open to ~25% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
• Deploy and maintain Scale software at customer sites
• Develop customer requested features and work closely with them to ensure that they win customer love.
• Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• 5+ years of full-time engineering experience, post-graduation
• 2+ years of prior engineering management or equivalent experience and has managed an engineering team.
• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.

• Prior experience developing with Python and JavaScript, or other modern software languages. Familiarity with Node and React is a plus.
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Linux experience: Understanding of shell scripting, operating systems, etc
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Understand unique DoD and USG constraints when it comes to technology

Scale AI’s Public Sector business is growing quickly as government agencies adopt AI to support critical national security, defense, and public sector missions. We’re looking for a hands-on Field Engineering Manager on the front lines leading a team of our field engineering efforts for our federal AI projects, having the opportunity to meaningfully impact millions of dollars in revenue by working closely with our largest public sector customers and ensuring that they become passionate, lifelong Scale customers. This role is ideal for someone who thrives in technical environments, enjoys managing teams while staying close to the code, and wants to work on meaningful problems that impact real world operations across the U.S. government. 

Field Engineers are software engineering generalists who enjoy working with clients directly, taking ambiguous requirements and issues, and quickly designing and building production-grade solutions in close collaboration with the Product, Engineering, and Delivery teams. Field Engineers are experts on Scale's products and codebase, and have general technical knowledge on GenAI systems, APIs, networking, and data engineering. Field Engineers are strong relationship builders, great project managers, and always fun to work with. You’ll play a critical role in delivering technical solutions—all while helping your team grow and execute.

You’ll split your time between technical planning and execution (50%) and people management and team development (50%), leading a team of 6-8 engineers. You’ll work cross-functionally with product, engineering, security, and delivery teams to ensure our engineering efforts meet complex federal compliance, security, and performance needs.

Day to day:

• 50% Field engineering - customer engagement, technical development and delivery 
• 50% Managing a growing team

You will:

• Recruit a high-performing engineering team. 
• Drive engineering productivity. Provide guidance, mentorship, and technical leadership to a team of customer facing engineers working on Generative AI projects. 
• Collaborating with cross-functional teams to define, design, and execute strategic roadmap based on customer needs.
• Work directly with customers to understand their problems and translate those into custom workflows within Scale’s platform.
• Be open to ~25% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Lead end-to-end technical delivery of custom workflows from scoping to development to testing to implementation
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• 5+ years of full-time engineering experience, post-graduation.
• 2+ years of prior engineering management or equivalent experience and previously managed an engineering team.
• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
• Prior experience developing with Python and JavaScript, or other modern software languages. 
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus.
• Linux experience: Understanding of shell scripting, operating systems, etc.
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) is a plus.
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.
• Understand unique DoD and USG constraints when it comes to technology.

Scale AI is seeking a highly skilled and motivated Mission Software Engineer to join our dynamic Federal Engineering team. As a part of this team, you will play a critical role in supporting Scale’s government customers by scoping and developing onsite solutions. Our scalable, high-performance platform is the foundation for these customer solutions, and your expertise will be instrumental in designing and implementing systems that can handle interactions with existing customer systems to help our products integrate into existing customer workflows.   

You will:

• Work directly with customers to understand their problems and translate those into features in Scale’s platform.
• Be open to >50% travel or relocation to a key customer geographic location.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Implement end-to-end data integrations, syncing customer’s data to Scale’s platform and back
• Deploy and maintain Scale software at customer sites
• Develop customer requested features and work closely with them to ensure that they win customer love.
• Build robust and reliable backend systems that can serve as standalone products, empowering customers to accelerate their own AI ambitions.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• This role will require an active TS/SCI security clearance or the ability to obtain a security clearance.

Ideally you have:

• Track record of success as a hybrid customer facing engineer, forward deployed software engineer, and ability to quickly adapt to different roles.
• Prior experience developing with Python and JavaScript, or other modern software languages. Familiarity with Node and React is a plus.
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Linux experience: Understanding of shell scripting, operating systems, etc
• Networking experience: Understanding of networking technologies, configuration  (ports, protocols, etc) 
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles

About Scale AI

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

Role Overview

As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Leadership & Collaboration

• Serve as the Engineering Manager and technical point of contact for strategic enterprise accounts
• Lead a team that is collaborating with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 5+ years of software engineering experience with 2+ yrs of  Management experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

Scale AI is seeking a highly skilled and motivated Software Engineer, Frontier AI Infrastructure to join our dynamic Public Sector Engineering team. As a part of this team, you will own the model inference layer - enabling state of the art models, debugging the latest AI tools, managing networking, debugging latency, and tracking pricing/usage metrics for AI models. You will lead technical discussions on the frontlines with cloud vendors and customers to deliver on critical contracts and to debug platform issues. You will also work upstream with Product to understand features before they break, moving us from "infra-only debugging" to proactive integration testing.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• You will work with Product to build integration tests that catch issues early, shifting the focus from "infra-only debugging" to preventing failures upstream.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have: 

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment.
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.

About Scale AI

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities.

Role Overview

As a Forward Deployed AI Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments.

This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows.

Key Responsibilities

Customer Integration & Deployment

• Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements
• Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
• Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows
• Deploy and configure AI models and agents within customer security and compliance boundaries

AI Agent Development

• Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation
• Architect multi-agent systems that orchestrate between different models, tools, and data sources
• Implement evaluation frameworks to measure agent performance and iterate toward business objectives
• Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement

Prompt Engineering & Optimization

• Create sophisticated prompt engineering strategies optimized for customer-specific domains and data
• Build and maintain prompt libraries, templates, and best practices for customer use cases
• Conduct systematic prompt experimentation and A/B testing to improve model outputs
• Implement RAG (Retrieval Augmented Generation) systems and fine-tuning pipelines where appropriate

Technical Leadership & Collaboration

• Serve as the primary technical point of contact for strategic enterprise accounts
• Collaborate with customer data scientists, ML engineers, and software developers to ensure smooth integration
• Provide technical training and knowledge transfer to customer teams
• Work closely with Scale's product and engineering teams to translate customer needs into product improvements
• Document technical architectures, integration patterns, and best practices

Problem Solving & Innovation

• Debug complex technical issues across the entire stack, from data pipelines to model outputs
• Rapidly prototype solutions to unblock customers and prove out new use cases
• Stay current on the latest AI/ML research and tools, bringing innovative approaches to customer problems
• Identify opportunities for productization based on common customer patterns

Required Qualifications

• 4+ years of software engineering experience with strong fundamentals in data structures, algorithms, and system design
• Production Python expertise with experience in modern ML/AI frameworks (e.g., LangChain, LlamaIndex, HuggingFace, OpenAI API)
• Experience with cloud platforms (AWS, GCP, or Azure) and modern data infrastructure
• Strong problem-solving skills with the ability to navigate ambiguous requirements and rapidly iterate toward solutions
• Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical audiences

Preferred Qualifications

Agent Development Wiz

• Deep understanding of LLMs including prompting techniques, embeddings, and RAG architectures
• Experience building and deploying AI agents or autonomous systems in production
• Knowledge of vector databases and semantic search systems
• Contributions to open-source AI/ML projects

Infrastructure Guru

• Experience with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience using Terraform, Bicep, or other Infrastructure as Code (IaC) tools
• Previous work in a devops, platform, or infra role
• Familiarity with enterprise security, compliance, and governance requirements (SOC 2, GDPR, HIPAA)

Customer Product Whisperer

• Proven ability to work with customers in a technical consulting, solutions engineering, or product engineering role
• Domain expertise in verticals like finance, healthcare, government, or manufacturing
• Experience with technical enablement or teaching programs

Sample Projects

The following are some examples of the types of projects we’ve worked on with customers. All of these projects leverage customer data, integrate directly into customers’ existing systems, and are deployed on their infrastructure.

Deep Research for Due Diligence

For a global professional services firm, we developed a sophisticated deep research agent to assist in due diligence. This agent employs a multi-agent architecture for robust fact-checking, integrates several internal MCP tools, and processes complex, unstructured data sources. This solution reliably saves employees hundreds of hours weekly.

Churn Prediction

Working with a TelCo organization, we built a model utilizing customer data to predict churn likelihood. The system then curates personalized offers based on this prediction. This model was integrated into a "next best action" copilot, enabling call center agents to proactively surface relevant offers to customers, leading to a significant reduction in churn.

Data Extraction Voice Agent

We partnered with a healthcare organization to create a lifelike voice agent and avatar designed to gather unstructured health information from patients. Engineered for low latency, the agent adeptly manages conversational flow, adheres to safety guardrails, and efficiently handles data extraction. This automation saves the organization's nurses hundreds of hours each week.

The Public Sector software engineers (SWEs) create the core product building blocks forward-deployed teams use to develop agentic capabilities that function across multiple domains. SWEs responsibilities include building the systems required to ingest and process federal datasets to support real-time decision-making in contested environments. We develop novel agentic enabling capabilities that includes:

• Create multi-layered guardrails around agents
• Optimize data retrieval for agents
• Orchestrate fleets of asynchronous agents
• Automatically alerts users to deviations in data
• Illustrating how an agent reached a decision

As a Staff Software Engineer, you will orchestrate the implementation of vertical features and horizontal capabilities to include mentoring other engineers on defining requirements with stakeholders and communication tradeoffs of technical implementations on feature and capabilities until they are accepted by the stakeholders.

You will: Orchestrate feature implementation across the Federal engineering team to ensure architectural consistency.

• Define technical strategy for agentic guardrails, explainability, and fleet orchestration.
• Ensure system reliability and performance across multiple security classifications and network types.
• Mentor engineers in the process of defining requirements with stakeholders and gathering acceptance.
• Communicate high-level technical trade-offs and implementation strategies to senior government stakeholders and Scale C-Suite members.
• Influence the long-term product strategy and technical roadmap for the Federal business unit.
• Consult on the architecture of AI-powered solutions for large-scale federal contracts.

Ideally you will have: 

• Full Stack Development: Proficiency in front-end, back-end development and infrastructure, including experience with modern web development frameworks, programming languages, and databases
• Cloud-Native Technologies: Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is a plus
• Data Engineering: Knowledge of ETL (Extract, Transform, Load) processes and experience in building data pipelines to integrate and process diverse data sources. Understanding of data modeling, data warehousing, and data governance principles
• AI Application Integration: Familiarity with integrating Large Language Models (LLMs) and building agentic workflows. Understanding of prompt engineering, retrieval-augmented generation (RAG), and agent orchestration is beneficial.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to defining and evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering

Scale AI is seeking a highly skilled and motivated Software Engineer, ARC (Architecture, Reliability, & Compute) to join our dynamic Public Sector Engineering team. As a part of this team, you will define how the company ships software, establishing the patterns for deploying into complex government and high-security environments, rather than just running Terraform scripts. You will build and maintain internal CLIs/tools that standardize testing, deployment, environment management and are tools that engineering relies on to prevent downstream breakages. You will execute on automated deployment efforts to pay down tech debt, creating fully functional staging/testing environments, and defining the company's standard for safe deployments.

You will:

• Design and implement secure scalable backend systems for Public Sector customers, leveraging Scale's modern and cloud-native AI infrastructure.
• Own services or systems and define their long-term health goals, while also improving the health of surrounding components.
• Re-architect the stack to run in compliant or restrictive environments. This requires designing swappable components (auth, storage, logging) to meet government/security mandates without breaking the product.
• Collaborate with cross-functional teams to define and execute the vision for backend solutions, ensuring they meet the unique needs of government agencies operating in secure environments.
• Participate actively in customer engagements, working closely with stakeholders to understand requirements and deliver innovative solutions.
• Contribute to the platform roadmap and product strategy for Scale AI's Public Sector business, playing a key role in shaping the future direction of our offerings.

Must have:

• At least an active secret clearance and the ability & willingness to up level to TS/SCI with CI Poly. This is a requirement and candidates will not be considered who do not hold at least a secret clearance

Ideally you'd have:

• Full Stack Development: Proficiency in both front-end and back-end development, including experience with modern web development frameworks, programming languages, and databases. Experience with developing & delivering software to air-gapped & isolated environments is a plus.
• Cloud-Native Technologies: Understanding of containerization (e.g., Docker) and container orchestration (e.g., Kubernetes) is desired. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience in developing and deploying applications in a cloud-native environment. 
• Security Focused: Experience with Federal Compliance frameworks, and requirements(e.g, Cloud SRG, FedRAMP, STIG Benchmarks, etc). Experience developing software & technical solutions that meet strict security & regulatory compliance requirements.
• Problem Solving: Strong analytical and problem-solving skills to understand complex challenges and devise effective solutions. Ability to think critically, identify root causes, and propose innovative approaches to overcome technical obstacles.
• Collaboration and Communication: Excellent interpersonal and communication skills to effectively collaborate with cross-functional teams, stakeholders, and customers. Ability to clearly articulate technical concepts to non-technical audiences and foster a collaborative work environment.
• Adaptability and Learning Agility: Willingness to embrace new technologies, learn new skills, and adapt to evolving project requirements. Ability to quickly grasp and apply new concepts and stay up-to-date with emerging trends in software engineering.
• Must be able to support work 3-4 days a week from the DC, SF, NYC, or STL office.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.  

The successful candidate will join the global Cloud Infrastructure team to design, build and support services and solutions to meet a wide variety of business requirements. You will be working closely with the trading, research and wider business teams to drive adoption of cloud-based services, implementing a cloud-first approach to problem solving. Cloud computing infrastructure is at the heart of QRT’s IT platform, and spans across many business areas including research technology, trading tools, market execution and data processing.

Your future role within QRT:

• Design and implement highly available, scalable, and secure cloud infrastructure on AWS
• Develop automation scripts to manage and maintain cloud infrastructure using tools such as Terraform and CloudFormation
• Monitor and optimize the performance and cost-effectiveness of cloud infrastructure
• Collaborate with development teams to support the deployment and operation of applications on AWS
• Evaluate and recommend new technologies to improve the reliability, scalability, and security of the company's cloud infrastructure
• Troubleshoot and resolve technical issues related to AWS infrastructure

Your present skillset:

• Extensive experience with AWS, including experience with EC2, S3, VPC, and other core services
• Proficiency with scripting languages (e.g. Python, Bash)
• Familiarity with configuration management tools (e.g. Ansible, Terraform)
• Experience with containers and orchestration technologies (e.g. Docker, ECS, Kubernetes)
• Experience with monitoring and performance tuning in a cloud environment
• Familiarity with agile software development methodologies
• Excellent communication and collaboration skills

Base salary range for this position is $150,000 to $220,000 per year. 

QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.  

You will join the Cloud Infrastructure team in New York. The team designs, builds, and operates cloud platforms that support trading and research workloads, including digital asset and crypto-related systems. The team works closely with development, trading, and operations teams to deliver secure, reliable and scalable cloud solutions.

Your Future Role within QRT

• Design and implement deployment strategies for applications on AWS in collaboration with development, trading and operations teams
• Drive the adoption of CI/CD practices to automate and streamline software delivery
• Develop and maintain monitoring solutions to ensure availability, performance and reliability of cloud-based applications
• Work with developers to enhance application scalability, reliability and security in cloud environments
• Provide operational support and troubleshooting for issues related to cloud deployments and infrastructure
• Evaluate and introduce new tools and technologies to improve efficiency of DevOps processes
• Act as a liaison between engineering and business teams to facilitate effective communication and collaboration

Your Present Skillset

• Extensive experience with AWS services and infrastructure (e.g. EC2, S3, VPC and related components)
• Proficiency in scripting languages such as Python or Bash for automation
• Strong understanding of CI/CD principles and experience with pipelines using tools such as Jenkins or GitLab CI
• Experience with infrastructure-as-code tools such as Terraform, CloudFormation or AWS CDK
• Hands-on experience with distributed computing systems and processing large datasets
• Practical experience with containerisation and orchestration (e.g. Docker, Kubernetes)
• Good understanding of Linux systems, including networking and performance optimisation
• Familiarity with time synchronisation concepts and protocols such as NTP or PTP
• Strong communication and collaboration skills, with the ability to work effectively across teams and departments

Base salary range for this position is $150,000 to $240,000 per year. 

QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

The Position

Our DevOps Engineer must have a strong technical background in Azure, development, and operations processes, as our firm implements an aggressive and exciting cloud strategy. This role will facilitate and develop streamlined processes and work collaboratively with cross-functional teams of software engineers, data engineers, product and project managers, business analysts, and infrastructure architects. This individual must thrive in a fast-paced environment and be self-motivated with a passion for problem-solving and innovation. Our IT department is project-focused, undergoing a complete digital business transformation for the firm. This position will drive new possibilities and opportunities for teams to learn cutting edge technologies while ensuring current systems are supported at their best.

Key Responsibilities

• Create and maintain highly scalable Azure infrastructure using Microsoft Bicep and PowerShell
• Create and maintain Azure DevOps YAML CI/CD pipelines and environments
• Assist with Azure infrastructure or application code related troubleshooting
• Maintain proper user access to infrastructure and applications with EntraID and Azure IAM
• Perform periodic application security and code quality reviews with Snyk and Sonar Cloud
• Create modern automated cloud first solutions
• Attend daily Agile Standup and report on work progress
• Assist IT teams with onboarding new Azure infrastructure
• Recommend best DevOps practices based on industry standards

Qualifications

• 3+ years of experience deploying and maintaining Azure PaaS resources
• 3+ years of experience with Azure DevOps Repos and Pipelines
• 3+ years of experience with languages such as PowerShell, C# and Python
• 2+ years of experience with Infrastructure as Code (AzureRM, Bicep, Terraform, etc)
• Experience with EntraID or AD, and Identity and Access Management (IAM)
• Familiarity with containerization (Docker, Azure Container Apps, AKS, etc)
• Familiarity with Atlassian product suite, i.e. Jira, Jira SM, and Confluence
• Ability to clearly articulate DevOps best practices and concepts to Development and IT Teams
• Ability to translate technical requirements into work product that meet business needs
• Microsoft Certification a big plus (AZ-104, AZ-204, AZ-305, AZ-400, AZ-500, AZ-900)
• Experience with shift left code security practices (Snyk, etc.) a big plus
• Experience with code quality tools (Sonar, etc.) a big plus
• Experience developing software a plus

Education

• Bachelor of science degree (or equivalent) in Computer Science, Engineering, or relevant field
• Experience in developing/engineering applications for a large company

Senior Fullstack Software Engineer - Experiences

Location: Soho, NYC / Remote
Department: Engineering

The Role

We’re looking for a Senior Fullstack Software Engineer to help architect, build, and scale the next generation of our Flowcode 2 Consumer Experiences. You will join our Experiences pod with a focus on creating amazing end user hub and landing page experiences that are dynamic and engaging. You’ll work across the stack — from contributing to backend services to building out dynamic end to end landing pages. Though this is a full stack position, we are looking for someone that has deep backend experience as well.

As one of the senior engineers on a small but highly capable team, you’ll own medium to large sized features, drive technical execution, contribute to a delivery focused environment, and mentor others. You’ll balance hands-on engineering with architectural thinking, helping us move fast while maintaining reliability, performance, and code quality.

This is an ideal role for a problem-solver who values simplicity over complexity, enjoys building dynamic and interactive applications and approaches engineering with pragmatism and curiosity.

What You’ll Do

• Design, build, and maintain scalable features across a modern front-end framework and backend services.
• With support, own key features end-to-end, from data design to user-facing experiences.
• Architect for growth — help drive your pods’s technical roadmap and shepherd established engineering best practices.
• Collaborate across teams with product, design, and data to deliver measure, deliver and grows features quickly and iteratively.
• Write clean, reliable, and maintainable code, with strong attention to performance, best practices and developer experience.
• Mentor engineers and help elevate technical execution across you pod.
• Stay pragmatic — balance ideal engineering with the realities of speed, customer needs, and startup resource constraints.
  
  

What We’re Looking For

• 5–7+ years of experience building and shipping production-quality software across the stack.
• Proficiency in at least one modern backend language (e.g., Go, Python, C#,, Java).
• Strong experience with React, Next.js, or other modern front-end frameworks. We use Svelte but any modern framework experience is welcome.
• Deep understanding of web architecture, API design, and data modeling in relational and/or NoSQL databases.
• Familiarity with cloud environments (AWS, GCP, or similar) and containerized deployment (Docker, Kubernetes).
• Commitment to code quality, with solid grounding in design patterns, testing, and CI/CD.
• Strong grasp of scalability and performance — able to make informed tradeoffs between speed and correctness.
• Excellent communication skills and a collaborative mindset.
• A builder’s mentality — comfortable taking initiative and owning outcomes from design through production.

Nice to Have

• Experience building consumer focused SaaS applications and experiences
• Experience with form based, dynamic applications with rich user generated content.

Flowcode is not for everyone. We hire with a pinhole lens — only those with the rare combination of intellectual horsepower, execution velocity, and uncompromising drive will thrive here. If you are seeking to operate at the highest levels of performance and impact, we want to meet you.

How to Apply

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

A successful candidate’s starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The current range for this role is up to $200-$220k plus equity. 

Staff Software Engineer - Platform

Location: Soho, NYC / Remote
Department: Engineering

The Role

We’re looking for a Staff Software Engineer to help grow and build the core platform that powers our Flowcode 2 application at scale. This role sits at the intersection of architecture, leadership, and pragmatic execution with a focus on creating and augmenting reliable, scalable, and extensible services and applications. 

You’ll operate as a technical leader with in our Platform pod, growing platform capabilities, building new features and problem solving in a dynamic and challenging technical environment.. While this is a hands-on role, it requires a strong bias toward backend systems, distributed architecture and deep technical leadership. We value the ability to guide teams toward pragmatic, high-impact solutions.

This role is ideal for an engineer who values simplicity, correctness, and pragmatism, and who can balance long-term platform investments with immediate business needs.

What You’ll Do

• Own critical systems end-to-end, including design, implementation and deployment,
• Hands on designing, building, and maintaining scalable features across a modern front-end framework and backend services.
• Architect for growth — help drive your pods’s technical roadmap and shepherd established engineering best practices.
• Collaborate across teams with product, design, and data to deliver measure, deliver and grows features quickly and iteratively.
• Mentor and guide senior engineers, raising the bar for technical execution and system design across teams.
• Balance ideal engineering with the realities of speed, customer needs, and startup resource constraints.
• Drive improvements in observability, performance, and incident response
• Advocate for pragmatic solutions, solving the right problems with the appropriate level of complexity.
  
  

What We’re Looking For

• 8+ years of experience building and operating production-grade systems, with a strong backend focus.
• Deep expertise in building high-performance, concurrent services.
• Proven experience designing and scaling distributed systems and service-oriented architectures.
• Strong understanding of API design, data modeling, and consistency tradeoffs Experience with cloud infrastructure (AWS, GCP, or similar) and modern deployment patterns (Docker, Kubernetes).
• Proficiency in several modern backend language (e.g., Go, Python, C#,, Java).
• Commitment to code quality, with solid grounding in design patterns, testing, and CI/CD.
• Strong grasp of scalability and performance, able to make informed tradeoffs between speed and correctness.
• Excellent communication skills and a collaborative mindset.
• A builder’s mentality, comfortable taking initiative and owning outcomes from design through production.
• A history of working with in 20+ person engineering organizations and collaborating with Product and Design to enable feature delivery at a reasonable velocity

Flowcode is not for everyone. We hire with a pinhole lens — only those with the rare combination of intellectual horsepower, execution velocity, and uncompromising drive will thrive here. If you are seeking to operate at the highest levels of performance and impact, we want to meet you.

How to Apply

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

A successful candidate’s starting pay will be determined based on the role, job-related skills, experience, qualifications, work location, and market conditions. The current range for this role is up to $280-$310k plus equity. 

The opportunity
Every day, we connect billions of players with the games and experiences they love.

Our Vector Gamer AI team sits at the heart of that mission, governing ad ranking and bidding decisions across billions of daily impressions, where large-scale machine learning and real-world impact converge at scale.

We're hiring a Staff Backend Engineer to build and operate the infrastructure those models depend on. You'll design and operate the distributed systems that power billions of daily decisions, with a focus on the performance, reliability, and scalability of inference systems.

Join us and help influence how billions of gaming experiences are discovered, monetized, and how creators are rewarded.

What you'll be doing

• Design, develop, and deploy production-grade backend services and distributed systems powering large-scale online model inference at billions of daily requests
• Drive technical direction of our inference platform, with a focus on low-latency, high-throughput serving infrastructure
• Partner with ML engineers to ensure online serving infrastructure scales with growing model complexity and inference volumes, without compromising latency or throughput
• Ensure the reliability, scalability, and efficiency of our systems in production using monitoring and observability tools like Prometheus and Grafana.
• Manage and optimize cloud infrastructure on GCP, orchestrating workloads with Kubernetes across a high-scale production environment
• Promote and implement best practices for backend service development, testing, deployment, and monitoring (DevOps, SRE).

What we're looking for

• 5+ years designing, deploying, and maintaining distributed systems at scale
• Expertise in Golang for building high-performance, low-latency backend infrastructure
• Hands-on experience with cloud infrastructure on GCP and workload orchestration with Kubernetes
• Strong grounding in monitoring and observability tooling, including Prometheus and Grafana
• Experience in ad tech, recommender systems, real-time personalization, or other performance-critical domains
• Familiarity with microservice architectures, containerization (Docker), and CI/CD best practices
• Familiarity with machine learning platforms, workflows, and serving infrastructure

You might also have

• Experience with ML inference servers like NVIDIA Triton Inference Server.
• Familiarity with auction mechanics or bidding systems in an ad tech context.
• Experience embracing AI as a strategic advantage in engineering, following established best practices for code quality and security.

Additional information

• Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.

Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.

While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program

Life at Unity
Unity [NYSE: U] is the world’s leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D — closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#SEN #LI-AR1

This is Hybrid role (3 days in office /2 days remote)

About your Team:

The Enterprise Architecture organization is looking for a Data Engineer to join the team and help build the next generation of data infrastructure and AI-enabled workflows. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines, data lake platforms, and analytics solutions that support enterprise-wide AI initiatives and advanced analytics capabilities. You will partner closely with internal development teams and IT leadership to architect data solutions that meet diverse use-cases across the organization. This role offers the opportunity to work with cutting-edge data technologies, AI knowledge bases, and cloud-native data platforms as we scale our data operations. Your work will focus on delivering robust, well-documented data solutions and establishing best practices for data engineering across the enterprise.

 What will be your responsibilities within IBKR: 

· Design, build, and maintain scalable data crawlers and ETL/ELT pipelines to ingest data from various sources including enterprise collaboration tools, web applications, and internal databases

· Develop and manage data lake platform infrastructure including S3-based storage, Iceberg tables, AWS Glue data catalog, and cloud data warehouse solutions for analytics workloads

· Build and optimize real-time streaming data pipelines using Kafka for event-driven analytics and data processing

· Create and maintain data transformation pipelines to clean, curate, and prepare data for analytics and AI/ML applications, supporting multiple data formats including structured, semi-structured, and unstructured data (text, images, audio, video)

· Develop Python-based applications for data ingestion, processing, and integration supporting Gen AI RAG workflows and knowledge base systems

· Collaborate with internal development teams, data scientists, and stakeholders to understand requirements, architect appropriate data solutions, and create comprehensive technical documentation

· Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and data quality

· Write clean, maintainable, well-tested code following software engineering and data engineering best practices

· Create comprehensive technical documentation for data pipelines, architectures, and platform capabilities

 What required skill’s you need:

· 6+ years of hands-on data engineering experience with modern data stack technologies

· Strong experience with AWS cloud services, particularly: S3, AWS Glue, Athena, EMR, Lambda

· Proficiency in Python for data processing, ETL, and application development

· Experience with PySpark on EMR for large-scale data processing

· Strong SQL skills for data analysis and transformation

· Experience building and maintaining ETL/ELT pipelines at scale

· Experience with Kafka for streaming data pipelines and real-time data processing

· Knowledge of data lake architectures and modern table formats (e.g., Iceberg)

· Experience with CI/CD practices using Git, version control systems, and containerization (Docker)

· Understanding of data modeling, data warehousing concepts, and analytics best practices

· Exceptional problem-solving and analytical skills

· Excellent collaboration and communication (verbal and written) skills

· Self-motivated with ability to work independently and manage multiple priorities

· Willingness and enthusiasm to learn AI/ML technologies, stay current with emerging data engineering trends

 To be successful in this position, you will have the following:

• Self-motivated and able to handle tasks with minimal supervision.
• Superb analytical and problem-solving skills.
• Excellent collaboration and communication (Verbal and written) skills.
• Outstanding organizational and time management skills.

Company Benefits & Perks

About the Role

As a seasoned Infrastructure Engineer, you will design, manage, and scale our high-performance computing environments. This role bridges the gap between traditional system
administration and modern platform engineering, focusing on reliability, automation, and the stringent security requirements of the financial services industry. You will be responsible for a
hybrid ecosystem that spans AWS cloud and on-premise systems, ensuring 99.99% uptime for mission-critical services and transactions.

What You’ll Do

• Linux Systems Engineering: Design and manage high-performance Linux environments including Ubuntu, RHEL, or Amazon Linux. Focus on tuning for low-  latency financial applications and system-level hardening
• Infrastructure as Code (IaC): Architect and maintain scalable cloud infrastructure using Terraform and Ansible, treating infrastructure as a software project with version control
  and peer reviews
• Hybrid Networking: Manage connectivity between cloud environments and on-premise systems, focusing on secure VPC design, VPNs, and routing
• On-Premise Management: Manage physical switches, routers, and firewalls, with an understanding of multicast, VLANs, and interface aggregation
• CI/CD & Release Engineering: Build and optimize deployment pipelines to ensure system updates, patches, and application code are deployed safely and frequently
• Observability & Reliability: Implement comprehensive monitoring (using Prometheus, Loki, and Grafana) to track system SLIs/SLOs and implement automated alerting or self-
  healing scripts
• Container Platform Management: Support and scale Docker / Podman environments, focusing on pod networking and container runtimes
• Infrastructure Security: Implement "shift-left" security, including OS-level hardening (SELinux, AppArmor), automated vulnerability scanning, and IAM policy refinement

What You’ll Need

• Education: Bachelor’s degree in Computer Science, Engineering, IT, or a related field
• Systems Expertise: 3+ years of experience in Linux Administration or Infrastructure Engineering
• System Internals: Deep knowledge of system performance profiling (e.g., top, iostat, strace) and comfort with Linux system fundamentals (i.e. Systemd, LVM, and Cron)
• Automation Proficiency: Strong proficiency in Ansible and Terraform for infrastructure and system automation. Bash and/or Python experience for custom tooling as required
• Cloud & Networking Fundamentals: Hands-on experience with AWS Networking fundamentals (VPCs, Routing Tables, and Nat Gateways). Solid understanding of TCP/IP, DNS, and routing protocols like BGP or OSPF
• Container Runtime: Experience with container runtimes in a Production environment (Docker / Podman, Docker Compose). Kubernetes experience is a plus
• Problem Solving: Ability to perform root-cause analysis on complex distributed systems
  
  Applicants must be authorized to work for any employer in the U.S. DriveWealth is unable to sponsor an employment Visa at this time.

Special Knowledge (Nice to Have, But Not Required)

• Compliance Knowledge: Experience working within regulated environments such as SOC2, or FINRA
• High-Availability Architecture: Experience building multi-region, failover-capable architectures for mission-critical financial transactions
• SDLC Architecture: Architecting deployment pipelines using GitHub actions, familiarity with AWS Secrets Manager for managing sensitive secrets, and other DevOps toolchain
  services
• Fintech Protocols: Basic understanding of financial messaging or low-latency requirements, such as FIX protocol
• Security & Application Tuning: Experience with WAF, DDoS mitigation strategies, and tuning edge application services such as HAProxy
• Certifications: CompTIA Linux+, RHCSA/RHCE, or AWS SysOps Administrator

What We're Looking For

As a Machine Learning Solutions Engineer, you will operate at the intersection of machine learning, distributed systems, and cloud infrastructure.
You will partner with customers to design and deploy end-to-end AI systems, spanning:

• Model development and training
• GPU infrastructure and cluster design
• Distributed inference and production deployment

This role goes beyond traditional ML solutions engineering—you will act as a technical architect, helping customers make critical decisions across compute, orchestration, and system design.

The role can be based out of our New York City or San Francisco office, with an in-office requirement of at least 2-3 days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this role at this time. The annual base pay range for this role is $150,000 - $195,000, in addition to a variable pay component and meaningful equity. 

What You’ll Do

Customer Architecture & Technical Leadership

• Partner with customers to understand ML workloads, infrastructure constraints, and scaling requirements
  
  
• Architect end-to-end solutions across:
  
  
• Data pipelines (CPU → GPU workflows)
  
  
• Distributed training (multi-node, multi-GPU)
  
  
• High-throughput inference systems
  
  
• Translate business goals (latency, cost, throughput) into technical system design decisions
  
  

GPU & Infrastructure Design

• Design and optimize workloads across GPU clusters (H100, H200, B200, etc.)
  
  
• Advise on:
  
  
• Training vs inference cluster design
  
  
• Interconnect choices (Ethernet vs Infiniband / RDMA vs Roce)
  
  
• Storage strategies (local NVMe vs networked / object storage)
  
  
• Model and optimize for:
  
  
• Tokens/sec, tokens/$
  
  
• Throughput vs latency tradeoffs
  
  
• GPU utilization and scheduling efficiency
  
  

Kubernetes & Platform Systems

• Design and support deployments on Kubernetes (EKS, GKE, on-prem clusters)
  
  
• Work with:
  
  
• GPU scheduling (time-slicing, MIG, bin-packing)
  
  
• Autoscaling and workload orchestration
  
  
• Helm-based deployments and multi-tenant environments
  
  
• Help customers balance:
  
  
• Raw Kubernetes flexibility vs platform abstraction (Lightning)
  
  

Demos, POCs, and Execution

• Build and deliver technical demos and POCs that showcase:
  
  
• Distributed training workflows
  
  
• Scalable inference endpoints
  
  
• End-to-end ML pipelines on Lightning AI
  
  
• Scope and lead POCs aligned to customer success metrics (latency, cost, reliability)
  
  

Cross-Functional Impact

• Act as the bridge between customers, product, and engineering
  
  
• Provide feedback on:
  
  
• Platform gaps in infrastructure, orchestration, and performance
  
  
• Emerging patterns in GPU usage and distributed systems
  
  
• Influence roadmap across ML workflows and infrastructure capabilities
  
  

Enablement & Thought Leadership

• Create technical content
• Architecture guides (e.g., high-throughput LLM inference systems)
• Best practices for GPU utilization and scaling
• Educate customers on modern AI infrastructure patterns

What You’ll Need

ML + Systems Expertise

• 3–6+ years experience in:
  
  
• Machine Learning / AI Engineering
  
  
• Solutions Engineering / Sales Engineering / ML Consulting
  
  
• Strong understanding of:
  
  
• Training vs inference workloads
  
  
• Model optimization (quantization, batching, caching, etc.)
  
  

GPU & Distributed Systems

• Experience working with:
  
  
• GPU clusters (NVIDIA stack preferred)
  
  
• Distributed training or inference systems
  
  
• Familiarity with:
  
  
• NCCL, CUDA, or GPU performance profiling
  
  
• Networking concepts (RDMA, Roce, Infiniband, high-throughput systems)
  
  

Kubernetes & Cloud Platforms

• Hands-on experience with:
  
  
• Kubernetes (EKS, GKE, or on-prem)
• Slurm 
• Containerization (Docker)
  
  
• Exposure to:
  
  
• GPU scheduling in Kubernetes environments
  
  
• Multi-tenant or production ML deployments
  
  

Programming & Tooling

• Strong Python skills (PyTorch preferred)
  
  
• Experience building:
  
  
• ML pipelines
  
  
• APIs or inference services
  
  
• Familiarity with Lightning AI, PyTorch Lightning, or similar frameworks is a plus
  
  

Customer-Facing Excellence

• • Ability to:
    
    
    • Explain complex infrastructure and ML tradeoffs clearly
      
      
    • Run technical discovery and uncover quantifiable success metrics
      
      
  • Experience working cross-functionally with:
    
    
    • Sales, product, and engineering teams

Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment. 

Our research spans:

• Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond. 
• Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
• Imaging foundation models trained across the world's largest microscopy datasets
• Reasoning and agentic systems that connect frontier LLMs with biological foundation models
• Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
• Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled

Join our Team!

As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible. 

What You'll Do

• Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
• Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
• Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
• Deploy models to production and manage artifact tracking across models and datasets.
• Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
• Work on simplification and improvement of codebase abstractions to accelerate research momentum.
• Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
• Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
• Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
• Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
• Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.

What You'll Bring

• Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
• Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
• Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience building or working with AI agent frameworks is a plus.
• A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.

Compensation

The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.

Benefits for the Whole You 

We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. 

• Provides a generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice. 
• Funding for select family-forming benefits. 
• Relocation support for employees who need assistance moving

Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time! 

#LI-Hybrid

What We're Looking For

We’re looking for a Backend Engineer to help develop and scale the Lightning AI platform, spanning APIs, infrastructure, billing, security, and integrations. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Extensive experience writing efficient, maintainable code in Go. Familiarity with best practices in testing, readability, and optimization is essential.
• Broad knowledge of backend and frontend systems, with experience building and scaling APIs, CLI tools, billing systems, and security protocols. Exposure to frontend frameworks is a plus.
• Experience with cloud platforms like AWS, GCP, or Azure and designing systems that are reliable, performant, and scalable. Familiarity with containerization (Docker, Kubernetes) is a strong advantage.
• Proven ability to take ownership of key features and drive end-to-end development
• Commitment to software quality, test automation, and continuous delivery. Experience proactively managing technical debt and speeding up time to production.
• Hands-on experience as a backend or product engineer in a SaaS technology company
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

 What You’ll Be Part Of

At iSpot.tv, we deal with BIG data, operating in a high-scale AWS environment with thousands of servers processing massive streams of media metadata. As a Senior SDE, you are a foundational pillar of our engineering team. You don't just write code; you own entire domains, drive scalable solutions, and act as a "go-to" expert.

We are currently looking for an AI-native engineer—someone who views AI not as a novelty, but as a core component of their development lifecycle—to help lead our mission-critical data evolution, including our strategic migration from Redshift to Snowflake.

 Your Impact

1. Technical Excellence & Domain Ownership

• Coding & Debugging: You will design domains with testability and multiple teams in mind, creating extensible and shareable codebases. You are expected to provide prescriptive code reviews that suggest more acceptable code patterns and contribute to company-wide style guidelines.
• System Modernization: You will lead efforts to upgrade legacy systems, refactoring technical debt into scalable, modern architectures, including x-region database migrations and moving to EKS.
• Quality & Release: You will maintain a high standard of quality, setting the example for the team. This involves developing the architecture for our automation systems and expertly debugging complex issues within the CI/CD pipeline. You will be responsible for implementing secure deployment strategies, especially for large-scale, high-risk projects.

2. AI-Driven Productivity & Innovation

• AI-First Mindset: You are expected to be "AI-native." You will actively explore and learn about AI technologies that enhance the efficiency of the entire team’s work.
• Leading Adoption: You don't just use AI; you "create space" for teammates to improve their AI tooling through pairing, providing demos, and writing documentation.
• Creative Problem Solving: You are a pioneer in critical technologies, bringing creative solutions to complex, large-scale projects and ensuring your contributions can be extended far into the future.

3. Operational Excellence & Data Strategy

• Data-Driven RCA: You will propose and implement viable domain measurement solutions. You’ll play a lead role in researching external solutions and leading root cause analysis (RCA) for complex, multi-domain incidents.
• Operational Efficiency & Toil Reduction: You are expected to proactively improve the current state of operations by identifying and reducing toil. You will apply a "Platform Engineering" mindset to automate repetitive manual tasks, ensuring the team remains focused on high-value engineering.
• Scalability & Influence: You will build internal networks to improve organizational speed and the quality of technology solutions, removing obstacles for the team as they arise. You are the "go-to" person for the team, identifying trends and introducing broad solutions to address systemic issues.
• Cost-Conscious Engineering: You will drive a mature cost-optimization strategy, ensuring that architectural decisions and cloud resource utilization are both performant and cost-efficient. You are expected to balance technical excellence with business value, treating cost-consciousness as a core pillar of system reliability.

4. Leadership & Collaboration

• Strategic Alignment: You routinely work cross-functionally to align partners and stakeholders with the project vision and strategy.
• Mentorship: You mentor less experienced team members, ensuring your communication promotes clarity and inspires action. You onboard and coach other engineers in adopting an AI-first mindset, focusing on low-risk strategies.
• Conflict Resolution: You are adept at handling personal conflicts within the team and navigating ambiguity to reach strategic milestones.

 What You Bring

• Experience: Significant experience developing software for shareable features across multiple engineering projects. Experience leading small-to-mid-sized technical initiatives is required.
• Architectural Leadership: Proven ability to make high-level architectural decisions, including redesigning legacy services to ensure they are highly reliable and operable. You follow industry best practices for high-availability API design and the streamlining of complex database operations.
• Platform Engineering: Hands-on experience with Platform Engineering principles, focusing on internal developer experience, infrastructure abstraction, and building self-service capabilities for engineering teams.
• Cloud Native: Expert knowledge of AWS (S3, Lambda, EC2, IAM).
• Tech Required: Java, Spring Boot, MySQL, RabbitMQ (or similar message broker), Kubernetes/EKS, Docker, CI/CD pipelines.
• Tech Preferred: Redshift, Helm, Terraform, Gradle, Groovy.
  • Bonus: Proven experience or a deep architectural understanding of migrating data workloads from Redshift to Snowflake.
• AI Native: Experience using AI coding assistants and LLMs to accelerate development (e.g., Kiro, Gemini, Copilot, Cursor, or similar).
• Soft Skills: Strong communication skills with the ability to tailor messaging to different audiences (from junior devs to senior leadership). Excellent problem-solving and analytical skills.

 Preferred Qualifications

• Experience in Ad-Tech or high-throughput "Big Data" processing environments.
• Experience with Infrastructure as Code (Terraform) and CI/CD concepts (CircleCI).

A track record of identifying trends in incidents and introducing broad solutions to address them.

Target cash compensation range: $136,100 - $170,000 USD Annually

We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full time iSpotters are eligible to participate in iSpot’s equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

For more information on total rewards package, go HERE

Hybrid & Flexible Workplace Policy

iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency. 

Those local or living in surrounding areas to one of our offices (Bellevue, WA or New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule. If you have questions regarding exact details of our hybrid & flexible workplace policy, please let your recruiter know and they will discuss with you further.

#LI-Hybrid

What You’ll Be Part Of

At iSpot.tv, we process massive streams of media metadata in a high-scale AWS environment. As an SDE II, you have moved past foundational learning and are now a competent, independent contributor. You are responsible for delivering high-quality features that power our industry-leading measurement and attribution products.

We are looking for an AI-native engineer—someone who instinctively uses AI to move faster and write better code. You will be a key player in our modern engineering culture, helping us maintain our "source-of-truth" data foundation while supporting major initiatives like our strategic migration to Snowflake.

Your Impact

1. Technical Excellence & Domain Ownership

• Coding & Debugging: You are competent in programming and debugging across multiple components and environments. You will independently own and deliver features, writing high-quality code that includes monitoring, metrics, and logging as standard practice.
• Testing & Quality: You author and own the testing plan for your features, considering product requirements and edge cases. You’ll perform various test types (unit, component, integration, E2E) and are developing the skills to identify patterns in test results to differentiate between application bugs and environment issues.
• Code Reviews: You actively participate in code reviews, following team guidelines and best practices to ensure the collective codebase remains healthy and maintainable.

2. AI-Driven Productivity & Efficiency

• AI-First Workflow: You independently use AI tools (e.g., Cursor, Copilot, Gemini) to improve the speed and quality of your tasks. This includes using AI for code understanding, self-code reviews, and ramping up quickly in new domains or languages.
• Critical Evaluation: You don't blindly copy-paste. You critically evaluate AI-generated output to ensure its correctness, security, and alignment with iSpot standards before relying on it.
• Continuous Improvement: You identify enhancements or efficiencies in your work assignments, using AI to automate repetitive tasks so you can focus on solving complex logic.

3. Operational Excellence & Data Strategy

• Incident Management: You participate in the on-call rotation and will contribute to defining on-call expectations. You are responsible for promptly investigating test failures and production alerts. You are also developing the ability to perform Root Cause Analysis (RCA) in common areas (code, technology, and incidents) with limited guidance.
• Scalability: You will build internal networks to improve organizational speed and improve the quality of technology solutions, removing obstacles for the team as they arise.
• Data Migration Support: You will support the senior team in our Redshift to Snowflake evolution by assisting with data validation, schema updates, and performance monitoring.

4. Collaboration & Growth

• Independence: You complete most assignments independently with little to no supervision, knowing exactly when and how to escalate issues to your manager or senior leads.
• Team Contribution: You help onboard and train new team members and are proactive in building trust through excellent follow-through and integrity.
• Communication: You communicate clearly and concisely, sharing opportunities to improve deliverables or work processes with the broader team.

What You Bring

• Experience: Significant experience (typically 2–5 years) developing software features for business or technology solutions.
• Java Proficiency: Strong experience with Java and Spring Boot in a microservices environment.
• Cloud Foundation: Solid understanding of AWS (S3, Lambda, EC2) and containerization (Docker).
• Tech Required: Java, Spring Boot, MySQL, Git, and familiarity with CI/CD pipelines.
• Tech Preferred: Experience with message brokers (RabbitMQ/SQS), Kubernetes (EKS), Docker, and SQL optimization.
• AI Native: Demonstrated ability to use LLMs and AI coding assistants to accelerate your development lifecycle.
• Mindset: A results-oriented drive to meet high standards and a "persistent/tenacious" approach to solving technical hurdles.
• Soft Skills: Strong communication skills with the ability to tailor messaging to different audiences (from junior devs to senior leadership). Excellent problem-solving and analytical skills.

Preferred Qualifications

Experience in Ad-Tech or high-throughput "Big Data" processing environments.

Target cash compensation range: $104,700 - 120,000 USD Annually

We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full time iSpotters are eligible to participate in iSpot’s equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

For more information on total rewards package, go HERE

Hybrid & Flexible Workplace Policy

iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency. 

Those local or living in surrounding areas to one of our offices (Bellevue, WA or New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule. If you have questions regarding exact details of our hybrid & flexible workplace policy, please let your recruiter know and they will discuss with you further.

#LI-Remote

About the Role

iCapital is looking for a Software Developer in Test to work on the iCapital platform. In this role, you’ll bring practical knowledge of agile development methodologies and engineering best practices. As a Software Developer in Test (SDET), you’ll work closely with the Development and Testing team. The ideal candidate would be a combination of a hands on developer who has some managerial experience, and who can understand existing automation test frameworks and has an ability to enhance and implement the same and should also be able to work with other engineers and product managers to support feature-based testing.

Responsibilities

• Build and implementation of robust automated test suites.
• Integration of automated test suites with the current build and deployment processes.
• Maintenance of automated tests to accommodate changes in system design and architecture.
• Integration of Automation framework with existing tools (JIRA).
• Create/Manage/Utilize Defect workflows with automated test execution.
• Design and publish meaningful metric to support automation test creation and execution.
• Build and implementation of performance test suites.
• Perform all types of testing – Functional. API, Automation, Performance and Load

Qualifications

• 8+ years of experience with QA engineering delivery experience
• 4+ years of delivery within Agile SDLC/teams ideally with CICD
• Programming experience in Java with focus on behavior driven development (BDD) and test-driven development (TDD) and design patterns, ideally within continuous integration (CICD)
• Experience with Java microservices and REST APIs and exposure to React front end
• Agile development approach
• Technologies: Java, JavaScript, IntelliJ/Eclipse
• CICD: Maven, Sonar, Git, Teamcity/Jenkins, Docker
• AI Integration experience preferred
• Exposure to banking and/or finance environments preferred
• Testing: Junit, Playwright, Protractor, JMeter or similar

The base salary range for this role is $110,000 to $145,000 depending on level.  iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).  

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. Every department has different needs, and some positions will be designated in-office jobs, based on their function.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ 

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. 

Who You Are:

Working as part of the derivatives engineering team, you are an expert on data pipelining and API development. You have knowledge surrounding common derivatives pricing frameworks and inputs for different tradable assets, and how these inputs are derived. You also have experience with working with various backend technologies and have a detailed working knowledge of core software engineering concepts, such as garbage collection, asynchronous processing, and data structures. You have experience in using mathematical and financial libraries (i.e. SciPy, NumPy, QuantLib) in software engineering applications. You are also familiar with building deployment processes for applications, including unit testing, integration testing, and deployment to a cloud provider (EC2, Kubernetes). You have a curiosity for learning new technologies and expanding your expertise across business lines and technology stacks.

As a team member, you will also work on production support issues and be involved in improvements on CI/CD automation and DevOps. 

Knowledge of the following is an advantage:

• Python, Go, Java
• Derivatives Pricing Models (SABR, SVI)
• Kafka, AWS SQS, or MQ
• Relational and non-relational Databases (Postgres, SQL Server, Databricks)
• Time series databases
• Spark
• FastAPI, Pydantic
• Jenkins
• AWS
• Caching Strategies and Implementations
• In-Memory Data Management
• Experience with Docker

What You’ll Do:

• Work closely with the Derivatives trading desk in optimizing their trading and risk management tools, as well as building reusable derivatives pricing libraries and algorithms
• Embrace and champion the thoughtful adoption of AI to improve team performance and business outcomes.
• Leverage AI tools (e.g., generative AI, automation platforms, data copilots) to improve productivity, decision-making, and output quality in your day-to-day work.

What We’re Looking For: 

• 6+ years of professional experience working in software development
• Experience with building data pipelines, APIs, and reporting tools
• Experience in Financial Technology
• Strong knowledge of data structures, their implementations, and optimization techniques
• University degree in computer science, physics, engineering, or equivalent programming experience

Bonus Points: 

• Experience with LLM Finetuning and RAG Optimization
• Full lifecycle development of a commercial system, including: requirements definition, agile planning, releasing, and production support
• Experience in quantitative trading

What We Offer:

• Competitive base salary and discretionary bonus
• Hybrid/Flexible Working Arrangements 
• Flexible Time Off (paid)
• 3% 401(k) company contribution
• Company-paid health and protective benefits for employees, partners, and other dependents
• Generous paid Parental Leave
• Competitive family planning benefits for US employees 
• Opportunities to learn about the Crypto industry
• Smart, entrepreneurial, and fun colleagues
• Free daily snacks and weekly breakfasts/lunches 
• Employee Resource Groups
• Free coaching and counseling sessions through Headspace

Apply now and join us on our mission to engineer a new economic paradigm.

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale. 

About the role:

As a Senior/Lead Forward Deployed Engineer (SFDE) at Parloa, you’ll be on the front lines of enterprise AI adoption - delivering cutting-edge technology into some of the most complex environments in the world. Your mission: lead end-to-end deployment projects from an engineering perspective - not just implementing what exists, but engineering what’s required to make it succeed at enterprise scale.

FDEs are our in-field product engineers. You will build what doesn’t yet exist, adapt architecture to enterprise realities, and engineer integrations across systems and APIs to make deployments successful. Your work is hands-on and code-first - you’ll be building, debugging, and engineering solutions directly in the field. What you ship not only makes deployments succeed, it also defines how customers experience Parloa and shapes what our product becomes.

This is not about maintenance. This is about engineering what makes it work in production, under real-world enterprise constraints, at speed and scale

Areas of ownership:

• Own deployment engineering projects: Lead the technical execution (incl. product engineering) of Parloa’s deployments inside large, complex enterprise environments
• Design for scale and resilience: Architect deployment solutions that meet enterprise-grade requirements for performance, reliability, and security
• Engineer solutions where none exist: Build custom extensions, integrations, and configurations to close product gaps and meet enterprise requirements
• Work across systems & stacks: Operate at the intersection of backend engineering, DevOps, and data engineering to ensure seamless delivery
• Partner with enterprise teams: Collaborate directly with customer engineering organizations to overcome constraints and deliver measurable outcomes
• Guide and mentor others: Collaborate with and provide technical guidance to more junior in-field engineers
• Influence at senior levels: Engage with enterprise architects and senior technical stakeholders, discussing solutions and architectures in depth to ensure alignment and credibility
• Debug under pressure: Rapidly unblock issues in mission-critical environments and ensure customer success.
• Shape the product: Act as the feedback loop between the field and our core engineering teams - turning deployment learnings into platform evolution
• Deliver long-term impact: Work closely with Deployment Strategists to ensure scalable architectures and durable customer value

Our Technology Stack: Python,TypeScript, Node.js, OpenAI, Microsoft Azure, Kubernetes, Docker, Terraform, MongoDB, MySQL, Redis, Kafka, MCP

Who you are:

• 7+ years of professional experience in software engineering, systems integration, DevOps, or data engineering roles with direct customer impact
• Proven track record of leading deep technical deployments and integrations in large-scale enterprise environments
• Strong technical depth across backend engineering, infrastructure-as-code, Kubernetes/cloud platforms, APIs, and databases - with proven experience in systems design and the ability to go hands-on in production systems
• Ability to operate independently in ambiguous, high-responsibility settings, especially when deploying live to enterprise systems
• A builder’s mindset with bias for action, creativity under pressure, and an obsession with making things work in the real world
• Degree in Computer Science, Engineering, or related technical field
• Strong plus: Experience building or integrating AI/LLM-powered systems (e.g., embedding agent workflows, vector databases, prompt orchestration)

Our recruiting process:

TA Screen → Hiring Manager Call → Technical Interview → Bar Raiser

Salary ranges include OTE

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

About Parloa

Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience, one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale.

About the role:

As a Forward Deployed Engineer, DevOps, your mission is to build and scale the dedicated infrastructure that powers our custom agent integrations for our most important customers. You will be the key technical cornerstone of our team, empowering our customer-facing Forward Deployed Engineers to build, deploy, and manage bespoke client solutions with speed and confidence. By creating a robust, automated, and self-service platform, you will directly enable the rapid delivery of high-quality, reliable custom services. 

Areas of ownership:

• Design, build, and maintain the cloud infrastructure specifically for hosting custom services developed by the Agent Integration Engineering team.
• Create flexible and reusable CI/CD pipeline templates that the integration team can easily adopt to automate the deployment of their services.
• Champion Infrastructure as Code to create standardized, yet customizable, service environments, ensuring consistency and rapid provisioning for new integrations.
• Manage a Kubernetes-based environment tailored for hosting a multitude of diverse integration services, focusing on security, isolation, and resource management.
• Implement robust monitoring and observability solutions to provide the integration team with deep visibility into the performance and health of their specific services.
• Serve as the primary DevOps partner for the Forward Deployed Engineering team, understanding their workflow, anticipating their needs, and removing infrastructure-related obstacles.
• Develop automation scripts (Python, Go, Bash) to streamline the entire lifecycle of custom integration services, from creation to decommissioning.
• Support and modernize legacy Azure infrastructure, helping transition workloads to a standardized, Kubernetes-based platform aligned with Parloa’s Engineering practices.

Who you are:

• 5+ years of professional experience in DevOps, infrastructure engineering, or a similar role.
• A strong customer-first mindset, viewing the Forward Deployed Engineering team as your primary customer.
• Proficiency in at least one scripting or programming language like Python, Go, or Bash.
• Hands-on expertise with a major cloud provider (AWS, GCP, or Azure).
• Advanced knowledge of containerization and orchestration, specifically Kubernetes, Helm, and Docker.
• Proven experience creating flexible CI pipelines with tools like Jenkins, GitHub Actions, or GitLab CI, and CD/GitOps workflows with tools like Argo CD.
• A strong background in Infrastructure as Code (Terraform is highly preferred).
• Experience building self-service tools and platforms that empower specific development teams.

Our recruiting process:

TA Screen → Hiring Manager Call → Technical Interview → Bar Raiser

Salary ranges includes OTE

Why Parloa?

We’re at the beginning of a new era in customer experience, one where AI doesn’t just respond, but understands, reasons, and takes action. We’re building agentic AI that enterprises trust with their most important customer moments: complex questions, high volumes, real stakes. When millions of people reach out to a brand, those interactions aren’t just support tickets; they’re defining experiences. We’re here to raise the standard: making every conversation seamless, intelligent, and genuinely helpful. If you care about shaping how businesses and customers connect at scale—and want your work to matter in real, everyday moments—this is where you do it.

At Parloa, ownership isn’t a buzzword; it means being accountable for outcomes, not just tasks. We operate in a category that’s evolving fast, where the bar is high, and the problems are complex. We hire people who think in solutions, communicate with clarity, and follow through. People who are comfortable making decisions, taking responsibility, and raising the standard for themselves and those around them.

We’ve grown beyond the earliest startup phase, but we’ve kept the intensity: fast execution, direct feedback, and a strong expectation to contribute meaningfully from day one.

Backed by leading global investors like General Catalyst, EQT Ventures, and Altimeter Capital, we’re scaling with a clear ambition: to become the global category leader in enterprise-grade conversational AI.

Location: Hybrid (Local to NYC area)

About the team

The Platform team at Capital Rx is made up of a set of passionate, motivated, and driven individuals who are not only experts in technologies but are great problems solvers and brings high energy and inspiration every day. The team always works a sense of ownership and urgency delivering highest quality of work ensuring seamless operations and fostering collaboration across the software engineering department. We own the architecture, framework & standards, infrastructure and CI/CD pipelines which development teams utilize to deliver code to Captial Rx’s Judi® platform. The team is also responsible for the production environment which requires knowledge with monitoring, alerting and on-call practices. The Platform team performs many functions whether that is tactical operations, providing general solutions for the enterprise or giving guidance or recommendations for individual product teams.

Position Summary:

We are a rapidly growing late-stage health tech company helping millions of lives through our innovative product Judi. We’re seeking a highly skilled and experienced Senior Platform Developer II to join our platform team. This pivotal role will be instrumental in building, scaling, and maintain the robust and secure infrastructure that powers our mission-critical platform.

You will be a force multiplier, enabling our development teams to deliver features faster and more reliably. You will champion infrastructure-as-code principles, contribute code to platform scalability, drive automation across the entire software development lifecycle, and ensure our platform meets the highest standards of scalability, performance, and security.

Position Responsibilities:

• Architect, implement, and maintain highly available, scalable, and secure platform & infrastructure
• Develop and maintain robust automation pipelines for continuous delivery (CI/CD), and infrastructure provisioning tools like GoCD, Harness, and Terraform
• Write clean, efficient, and well-tested Python code for automation, tooling and service development.
• Manage and optimize relational or in-memory databases, including PostgreSQL, Redshift and Redis, ensuring high performance, reliability, and data integrity.
• Administer and finetune container orchestration platforms such EKS and ECS.
• Implement and manage serverless architectures leveraging AWS Lambda for various platform functionalities.
• Collaborate closely with development teams to ensure infrastructure aligns with application requirements and best practices.
• Lead efforts in defining and enforcing security best practices across the platform, including adherence to HIPAA standards, FISMA, SOC II, and FedRAMP compliance standards.
• Monitor systems performance, identify bottlenecks, and implement proactive solutions to ensure optimal operation and scalability.
• Participate in on-call rotations to provide operational support and incident response.
• Champion Agile/Scrum methodologies, actively participating in sprint planning, stand-ups, and retrospectives.
• Mentor junior developers and contribute to a culture of technical excellence and continuous improvement.
• Evaluate and recommend new technologies and tools to enhance platform capabilities and efficiency.
• Develop internal tooling and automation scripts using Python and work with SQL to support operational workflows.
• Implement observability (monitoring/logging/alerting) best practices for highly available SaaS services.
• Responsible for adherence to the Capital Rx Code of Conduct including reporting of noncompliance.

Requirements

• 8+ years of experience as a Platform Engineer, DevOps Engineer, or Site Reliability Engineer.
• Deep expertise in AWS infrastructure and services including but not limited to EC2, Lambda, ECS, EKS, RDS, S3, VPC, CloudWatch, SQS, SNS, IAM, Kinesis
• Excellent proficiency with Terraform, Python, SQL, and automation tooling.
• Extensive experience with Docker and container orchestration (Kubernetes/EKS).
• Solid understanding and hands-on experience with SQL, database administration (PostgreSQL preferred), and performance tuning
• Experience with CI/CD systems (e.g., GoCD, GitHub Actions, Harness).
• Proven experience in automating Observability & Monitoring (Grafana, Kibana, Prometheus), standardizing incident response for alerts to maintain SLAs and SLOs
• Hands-on experience in environments compliant with FISMA, SOC 2, and/or FedRAMP.
• Background in building highly scalable, performant SaaS platforms.
• Excellent communication, collaboration and problem-solving skills.
• Ability to work effectively with cross-functional teams, including developers, IT security & compliance, product manager, and scrum masters.
• Strong experience in production on call rotations and responding to alerts.

This position description is designed to be flexible, allowing management the opportunity to assign or reassign duties and responsibilities as needed to best meet organizational goals.

Location: Preferably Hybrid (Local to NYC area) or Remote (For Non-Local)

About the team

The Platform team at Capital Rx is made up of a set of passionate, motivated, and driven individuals who are not only experts in technologies but are great problems solvers and brings high energy and inspiration every day. The team always works a sense of ownership and urgency delivering highest quality of work ensuring seamless operations and fostering collaboration across the software engineering department. We own the architecture, framework & standards, infrastructure and CI/CD pipelines which development teams utilize to deliver code to Captial Rx’s Judi® platform. The team is also responsible for the production environment which requires knowledge with monitoring, alerting and on-call practices. The Platform team performs many functions whether that is tactical operations, providing general solutions for the enterprise or giving guidance or recommendations for individual product teams.

Position Summary:

We are a rapidly growing late-stage health tech company helping millions of lives through our innovative product Judi. We’re seeking a highly skilled and experienced Platform Developer to join our platform team. This pivotal role will be instrumental in building, scaling, and maintain the robust and secure infrastructure that powers our mission-critical platform.

You will be a force multiplier, enabling our development teams to deliver features faster and more reliably. You will champion infrastructure-as-code principles, contribute code to platform scalability, drive automation across the entire software development lifecycle, and ensure our platform meets the highest standards of scalability, performance, and security.

Position Responsibilities:

• Develop and support highly available, scalable, and secure platform & infrastructure
• Develop and maintain robust automation pipelines for continuous delivery (CI/CD), and infrastructure provisioning tools like GoCD, Harness, and Terraform
• Write clean, efficient, and well-tested Python code for automation, tooling and service development.
• Manage and optimize relational or in-memory databases, including PostgreSQL, Redshift and Redis, ensuring high performance, reliability, and data integrity.
• Administer and finetune container orchestration platforms such EKS and ECS.
• Implement and manage serverless architectures leveraging AWS Lambda for various platform functionalities.
• Collaborate closely with development teams to ensure infrastructure aligns with application requirements and best practices.
• Contribute to defining and enforcing security best practices across the platform, including adherence to HIPAA standards, FISMA, SOC II, and FedRAMP compliance standards.
• Monitor systems performance, identify bottlenecks, and implement proactive solutions to ensure optimal operation and scalability.
• Participate in on-call rotations to provide operational support and incident response.
• Adopt Agile/Scrum methodologies, actively participating in sprint planning, stand-ups, and retrospectives.
• Evaluate and recommend new technologies and tools to enhance platform capabilities and efficiency.
• Develop internal tooling and automation scripts using Python and work with SQL to support operational workflows.
• Implement observability (monitoring/logging/alerting) best practices for highly available SaaS services.

Requirements

• 5+ years of experience as a Platform Engineer, DevOps Engineer, or Site Reliability Engineer.
• Strong expertise in AWS infrastructure and services including but not limited to EC2, Lambda, ECS, EKS, RDS, S3, VPC, CloudWatch, SQS, SNS, IAM, Kinesis
• Excellent proficiency with Terraform, Python, SQL, and automation tooling.
• Extensive experience with Docker and container orchestration (Kubernetes/EKS).
• Solid understanding and hands-on experience with SQL, database administration (PostgreSQL preferred), and performance tuning
• Experience with CI/CD systems (e.g., GoCD, GitHub Actions, Harness).
• Proven experience in automating Observability & Monitoring (Grafana, Kibana, Prometheus), standardizing incident response for alerts to maintain SLAs and SLOs
• Hands-on experience in environments compliant with FISMA, SOC 2, and/or FedRAMP.
• Background in building highly scalable, performant SaaS platforms.
• Excellent communication, collaboration and problem-solving skills.
• Ability to work effectively with cross-functional teams, including developers, IT security & compliance, product manager, and scrum masters.
• Strong experience in production on call rotations and responding to alerts.

This position description is designed to be flexible, allowing management the opportunity to assign or reassign duties and responsibilities as needed to best meet organizational goals.

About the Role

The Onsite Customer Growth team develops features that help Attentive’s customers grow through personalized experiences built directly on their websites. We focus on increasing list growth through investments in creative capabilities, experimentation, and AI-driven optimization. Our team builds the systems and product experiences that power onsite engagement for millions of users and help brands convert more visitors into subscribers and customers.

We’re looking for a Senior Software Engineer to help lead the design and development of the products and platform capabilities behind Attentive’s onsite growth experiences. This role can be oriented toward backend or full-stack engineering, depending on your strengths, but in either case you’ll be expected to own meaningful technical decisions, build scalable systems, and collaborate closely with product, design, data, and AI partners to deliver high-impact customer outcomes.

This hybrid role is based in our New York office, with in-office collaboration Tuesday through Thursday each week.

What You’ll Accomplish

• Design, build, and evolve scalable backend services, APIs, and user-facing product capabilities that power Attentive’s onsite growth products.
• Lead technical design for new features and platform improvements, making thoughtful tradeoffs around reliability, performance, maintainability, and speed of execution.
• Partner closely with product, design, AI, and data teams to develop intelligent, data-driven capabilities that improve performance and user experience for customers and end users.
• Anticipate future product and platform needs, and proactively design solutions that support team growth, product expansion, and increasing scale.
• Improve system observability, resiliency, and performance to ensure our onsite experiences remain fast, reliable, and effective at scale.
• Serve as a technical leader on the team by driving design discussions, raising the engineering bar in code reviews, and mentoring other engineers.
• Contribute to a strong engineering culture through high-quality implementation, pragmatic architecture, and a focus on measurable customer impact.

Your Expertise

• 5+ years of professional software engineering experience, ideally with strong experience building backend systems, product platforms, or customer-facing applications at scale.
• Strong proficiency in at least one modern programming language such as Java, or TypeScript
• Experience designing and operating distributed systems, APIs, and microservices, with a solid understanding of reliability, scalability, and performance.
• For backend candidates: deep experience building service-oriented systems and data-intensive applications.
• For full-stack candidates: strong backend fundamentals plus experience building high-quality frontend applications and collaborating closely on end-user experience.
• Experience with cloud infrastructure and modern developer tooling, such as AWS, Docker, Kubernetes, relational databases, caching systems, queues, or streaming platforms.
• Ability to translate business goals and product ideas into clear technical plans and execute effectively across functions.
• A track record of writing clean, maintainable, well-tested code and holding a high bar for production quality.
• Curiosity, strong collaboration skills, and a passion for building products that drive meaningful customer growth.

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $170,000 - $230,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-AB2

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About the Role
The Onsite Customer Growth team builds the features that help Attentive’s customers grow directly on their websites. Our mission is to accelerate list growth and improve conversion by delivering creative, high performing onsite experiences powered by strong engineering and intelligent AI driven optimization.

What You’ll Accomplish

• Lead, mentor, and grow a high performing engineering team responsible for building the backend systems powering onsite customer growth products
• Set the technical vision and roadmap for backend services, APIs, and data driven systems that power personalized onsite experiences at scale
• Partner closely with AI, data, and product teams to develop intelligent capabilities that improve performance and user experience
• Ensure the reliability, scalability, and performance of the systems that support customer growth and real time user interactions
• Drive best practices in design discussions, code reviews, architecture decision making, and operational excellence
• Foster a learning oriented team culture that encourages collaboration, curiosity, ownership, and continuous improvement
• Own delivery of key product initiatives, balancing long term platform investments with near term business objectives
• Promote clean, maintainable, well tested code and high engineering standards across the team

Your Expertise

• 7+ years of professional backend software engineering experience, including at least two years managing or leading engineers
• Strong proficiency in one or more modern programming languages such as Java, or Typescript
• Experience designing and operating distributed systems, APIs, and microservice architectures at scale
• Hands on familiarity with cloud platforms such as AWS and containerization technologies such as Docker or Kubernetes
• Deep understanding of databases, messaging systems, or streaming technologies such as PostgreSQL, Redis, or Kafka
• Track record of building reliable, scalable, high throughput systems that support customer facing products
• Demonstrated ability to coach and develop engineers, drive team alignment, and create an inclusive, collaborative engineering environment
• Strong communication and cross functional partnership skills, with the ability to work effectively with AI, data, product, and design teams
• A mindset rooted in ownership, curiosity, and a passion for building meaningful systems that drive measurable customer impact

What We Use

• Our infrastructure runs primarily in Kubernetes hosted in AWS’s EKS
• Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm
• Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS
• Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright
• Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, and Pandas

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $193,000 - $250,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MN1

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About the Role

The New York Times is looking for a Software Engineer to join our Scoop Core team. Our mission is to empower product teams with a modern platform that serves as the single source for all content.

Our platform enables teams to manage and evolve content schemas quickly and safely, while also providing the foundation for building user-friendly collaborative editing and publishing tools.

We use GraphQL for Schema Definition and queries, Golang for development and PostgreSQL for data storage. We host our platform services on AWS. We also maintain the existing legacy publishing platforms that are hosted on GCP.

You will report to the Senior Engineering Manager, Scoop Core.

Responsibilities:

• Take on multiple technical tasks not limited to programming, such as working with Cloud services, platforms and APIs
• Research and document proposed solutions
• Write unit tests, integration tests and user documentation
• Assist other teams to onboard to our platform
• Maintain existing legacy systems
• Collaborate and learn through pairing, design reviews, and code reviews
• Collaborate with Product Management and other professionals within your team and across the organization
• Demonstrate support and understanding of our value of journalistic independence and a commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• You have 2+ years of experience building large-scale software applications
• You have experience building backend systems
• You have hands-on unit and integration testing experience
• You have experience communicating updates and resolutions to customers and cross-functional partners

Preferred Qualifications:

#LI-Hybrid

REQ-019826

About the Role

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning Platform (MLP) team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models with low-latency and Service Level Agreements (SLAs) guaranteed by the MLP.

We are looking for a Software Engineer, with a focus on MLOps, to join our Machine Learning Platform team to help solve creative challenges around Machine Learning infrastructure for the New York Times.

This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.

Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform at scale

• You will build infrastructure to train and test algorithms that provide real-time content recommendations and personalization

• You will enhance ML platform's CI/CD and integration testing capabilities

• You will promote developer productivity by rolling out capabilities that maximize self-sufficiency and minimize the toil in learning those capabilities in building scalable applications with high speed, quality, and performance

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 2+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment

• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)

• Experience working with Kubernetes, Docker, and CI/CD

• Familiarity with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, Drone, Triton, TensorFlow, scikit-learn, DataDog

• Experience building real-world machine learning applications like recommendation systems, bandits, etc.

• Experience engaging with stakeholders to understand pain points, observe patterns, and identify opportunities for improvements

This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

REQ-019501

#LI-Hybrid

About the Role, Mission or Department Overview

The New AI Products and Platforms mission is a central hub for new, high-ambition AI opportunities and services at The Times. We are hiring a Senior Software Engineer to help build the backend services and infrastructure that will form our internal AI Platform.

This platform will enable teams across the company to build, deploy, and manage applications that use large language models (LLMs) to advance our journalism and our business. You will report to the Director of AI Platforms and work with a team of engineers, designers, product and project managers, data scientists, and newsroom stakeholders to make investments in AI possible across The Times.

This is a hybrid position based in our New York City headquarters. You can typically expect to come into the office two days per week.

Responsibilities:

• Design, build, and maintain scalable and reliable backend services and APIs for a central platform used by teams building AI applications across our journalism and our business.

• Take ownership of core platform components and integrations, including systems for prompt and workflow management, evaluation and tracing, and monitoring for cost, usage, and performance.

• Build and operate vector database and retrieval infrastructure to support search and AI-powered discovery experiences.

• Design and develop retrieval-augmented generation (RAG) pipelines and agentic workflows that connect our content, data, and AI models.

• Build orchestration layers for multi-step AI workflows, managing the coordination of LLM calls, retrieval, and business logic.

• Develop the infrastructure that enables teams to create and manage their AI applications, complete with metadata, observability, and access controls.

• Architect and implement data pipelines and storage solutions to support our AI systems.

• Write high-quality, maintainable, and well-tested code, primarily in backend languages like Python or Go.

• Ensure a high degree of code quality, security, and system observability.

• Collaborate with editorial, product, ML, and data teams to translate requirements into platform capabilities.

• Review code written by other software engineers on the team and provide feedback.

• Contribute to and advocate for robust testing strategies to ensure service reliability.

• Be a mentor to other software engineers to enable their growth.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 5+ years of software engineering experience, with a strong focus on backend development.

• 5+ years of experience in one or more backend programming languages such as Python or Go.

• 5+ years of experience designing, building, and operating distributed systems and APIs at scale.

• 1+ years of experience building applications with Large Language Models (LLMs) and familiarity with the surrounding ecosystem (e.g., orchestration, retrieval-augmented generation).

Preferred Qualifications:

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-Hybrid

REQ-019837

About the Role:

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning & AI team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements guaranteed by our platform.

As an MLOps Engineer you will partner with product, data science and ML platform engineers to build and maintain the infrastructure that powers the machine learning lifecycle. You will automate and refine the training, deployment, monitoring, and management of our ML models.

This role reports to the Senior Engineering Manager of Data Management Infrastructure.

Responsibilities:

• Build and Automate ML Pipelines: by owning robust CI/CD pipelines for automated model training, validation, deployment, and retraining.

• Productionalize Models: Build the process for packaging, containerizing, and deploying ML models as scalable, low-latency, and highly-available services.

• Monitoring and Operations: Implement and manage comprehensive monitoring for production models, tracking system health, data drift, and model performance degradation.

• Tooling and Infrastructure: Manage and evolve our MLOps toolchain, including model registries, feature stores, experiment tracking systems, and model serving platforms.

• Collaboration and Support: Partner with data scientists to understand model requirements and optimize them for production. Support software engineers in integrating with ML services.

• Best Practices and Governance: Champion and enforce MLOps best practices for reproducibility, versioning (data, code, model), testing, and governance.

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Basic Qualifications:

• 2+ years of software engineering or DevOps experience with a focus on MLOps, automation, and infrastructure

• 2+ years of experience programming in Python or Go

• Experience building and managing CI/CD pipelines (e.g., Github Actions, Jenkins, GitLab CI)

• Hands-on experience with containerization and orchestration (e.g., Docker, Kubernetes)

• Cloud platform experience (AWS, GCP) and familiarity with infrastructure-as-code (e.g., Terraform, CloudFormation)

Preferred Qualifications:

• Experience with MLOps tools (e.g., MLflow, Kubeflow)

• Experience with the machine learning model lifecycle, from experimentation to production

• Experience with data processing frameworks (e.g., Spark, Dask, or Ray)

• Experience with low-latency no-sql datastores (BigTable, Dynamo, etc)

• Familiarity with monitoring and observability stacks (e.g., Prometheus, Grafana, Datadog, or ELK)

• Knowledge of data engineering pipelines and orchestration tools (e.g., Airflow, Prefect)

REQ-019522

#LI-hybrid

About the Role

The New York Times is looking for a Senior Software Engineer, with a focus on ML platform development, to join our Machine Learning & AI team to help solve creative challenges around Machine Learning infrastructure.

Machine Learning (ML) at the New York Times enhances the experience of our 150 million digital readers from around the globe and grows our subscriber base through content recommendations and personalizations.

The Machine Learning & AI team builds and maintains the infrastructure that hosts all of The New York Times real-time ML inference models, including both data and compute. Our partners are Data Scientists that build and deploy their ML models on the ML platform. On the other end, our partners are engineering systems that call these hosted models at scale with low-latency and Service Level Agreements (SLAs) guaranteed by our platform.

This role is a hybrid role, based in New York City. You will report to the Engineering Manager of the Machine Learning Platform team.

Responsibilities:

• You will research, develop, and deploy infrastructure for the Machine Learning Platform that supports large-scale multi-tenant workloads

• You will build a platform to train and test algorithms that provide real-time content recommendations and personalization to our readers

• You will enhance ML platform's CI/CD and integration testing capabilities

• You will build a platform that supports the full Machine Learning workflow; from model training, testing and production deployment at high scale and low latency

• Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world

Basic Qualifications:

• 5+ years of direct relevant experience in MLOps or DevOps, including experience operating large systems in a production environment

• Experience deploying and monitoring systems using cloud infrastructure (GCP or AWS)

• Experience working with Kubernetes, Docker, and CI/CD (Drone, Argo, Jenkins, etc)

• Experience leading the development of large-scale, data-driven, distributed multi-tenant systems

• Proficiency with at least one high-level programming language like Python or Go

Preferred Qualifications:

• Experience with any of the these technologies: Terraform, Airflow, SQL/BigQuery, BigTable or other NoSQL datastores such as Cassandra, DynamoDB, Redis

• Familiarity with ML tooling such as Triton, TensorFlow, scikit-learn

• Experience building the infrastructure that power real-world machine learning applications like recommendation systems, bandits, etc.

• Experience engaging with partners to understand pain points, observe patterns, and identify opportunities for improvements

This role requires limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

REQ-019502

#LI-hybrid

About the Role

The Reflections team at The New York Times is looking for a Backend Software Engineer. You will be part of a diverse team that includes native mobile engineers, web/backend engineers, QA, product managers, designers and data experts.

The Reflections team focuses on personalizing the Times experience, making it feel "yours." We aim to help users effortlessly discover and regularly engage with the journalism they value most, strengthening. and deepening their relationship with the Times.

This role is hybrid, located at our New York City headquarters, and typically requires coming into the office two days per week.

Responsibilities:

• Collaborate with design, product, web, backend, and native mobile engineers to refine requirements and develop new features across our platform.
  
  
• Design, build, and maintain backend services primarily in Go (Golang), developing scalable REST or GraphQL APIs and writing high-quality, production-ready code following engineering best practices.
  
  
• Develop and improve Go-based services and microservices, integrating with databases, internal systems, and cloud infrastructure.
  
  
• Contribute ideas that help shape the direction of our products and actively participate in solving meaningful technical challenges.
  
  
• Participate in technical discussions and architecture decisions with native mobile, web, and backend engineers, as well as owners of internal and external dependencies.
  
  
• Work across multiple parts of the stack when needed while maintaining a strong focus on backend service development in Go.
  
  
• Provide production support by participating in on-call rotations for the services and systems we build.
  
  
• Contribute to iteration on internal team processes and norms.
  
  
• Demonstrate support and understanding of our value of journalistic independence and a commitment to our mission to seek the truth and help people understand the world.
  
  
• You will report to the Engineering Manager
  
  

Basic Qualifications:

• 3+ years of full-time experience developing backend APIs using Go (Golang), including building REST or GraphQL services in production environments. Experience with additional backend technologies such as TypeScript, Node.js, or Express is a plus.
  
  
• 3+ years of experience working with SQL or NoSQL databases, such as PostgreSQL or DynamoDB, including designing schemas, writing queries, and integrating data storage with backend services.
  
  
• 3+ years of experience building and deploying services on public cloud platforms, such as Google Cloud Platform (GCP) or Amazon Web Services (AWS).
  
  
• Experience working in Agile software development environments, collaborating with cross-functional teams through iterative development, testing, and release cycles.

Preferred Qualifications:

• Familiarity with GraphQL.
  
  
• Familiarity with containers and container orchestration systems like Kubernetes, Docker.
  
  
• Familiarity with CI/CD techniques and tooling (e.g. Jenkins, drone), automated testing and deployments, and other DevOps practices.
  
  
• Understanding of caching and content delivery.
  
  

This role will require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables. This role also requires availability to our core working hours which are 10am - 6pm ET.

#LI-Hybrid

REQ-019607

About the Role

The Quality Engineering team at The New York Times is hiring a QA Engineer. You will work with software engineers, DevOps, product managers, and designers to support quality across our web, mobile, and API platforms.

You will develop automated test frameworks, strengthen CI/CD reliability, and improve release confidence through scalable automation practices.

This role is hybrid and based in New York City, with an expectation of two days per week in the office. You will report to the Senior QA Manager.

Responsibilities:

• Design automated testing frameworks in Python for APIs, web, and mobile applications
• Develop and integrate automated test workflows into CI/CD pipelines
• Improve test reliability, execution speed, and coverage across environments
• Develop scalable test environments using containerization and cloud infrastructure
• Collaborate with engineering, DevOps, and product teams to define test strategies early in the development lifecycle
• Integrate logging, monitoring, and metrics into testing workflows to improve defect detection and release confidence
• Contribute to documentation and standards for automation and TestOps

Basic Qualifications:

• 3 years of experience in test automation, software engineering, or quality engineering
• Proficiency in Python and experience building maintainable automation frameworks
• 3 years of experience with modern test automation tools such as PyTest, Playwright, Selenium, or Appium
• 3 years of experience testing REST, GraphQL, or gRPC APIs
• Hands-on experience integrating automated tests into CI/CD pipelines (e.g., GitHub Actions, Jenkins, GitLab CI)
• 3 years of experience with Docker and familiarity with Kubernetes
• 3 years of experience working in cloud environments (AWS, GCP, or Azure)

Preferred Qualifications:

• Experience with mobile test automation
• Experience with test environment provisioning and infrastructure-as-code
• Familiarity with AI-assisted coding tools (e.g., GitHub Copilot, Cursor, Claude) in software development workflows
• Experience improving observability or quality metrics within engineering teams

#LI-Hybrid

REQ-019672

Octus is seeking a Principal Data Engineer to roll up their sleeves and build scalable, production-grade data pipelines and infrastructure. You'll be a hands-on technical leader — writing code daily, solving hard engineering problems, and helping elevate the team around you through doing. Spanning Snowflake, Databricks, and AWS, you'll be deeply involved in the day-to-day development of the data platform that powers Octus's products, data, and automation initiatives. The ideal candidate is an expert in Python and SQL who thrives in an execution-focused environment and has deep experience building modern data pipelines and lakehouse solutions.

Responsibilities

• Build and maintain end-to-end data pipelines — from raw ingestion through transformation and delivery — across diverse data sources (APIs, web data, internal feeds, etc.).
• Hands-on development of scalable, production-grade pipelines within Databricks, including Delta Lake table management, Workflows, and cluster optimization.
• Build and maintain data models, schemas, and transformation logic in Snowflake, optimizing for performance and reliability.
• Develop and manage Databricks environments including Unity Catalog, Delta Live Tables, and integration patterns that support both internal data consumers and external sharing use cases.
• Build and manage orchestration workflows using AWS services (MWAA/Airflow, Lambda, ECS, SQS, MSK) and Databricks-native orchestration where appropriate.
• Implement and maintain infrastructure as code (IaC) using Terraform, ensuring reproducibility and compliance with cloud standards.
• Establish and enforce best practices in data modeling, schema design, and ETL/ELT processes for high-volume structured and semi-structured data across Snowflake and Databricks.
• Ensure data quality, lineage, and observability through automated testing, monitoring, and alerting across all pipeline layers.
• Collaborate closely with technology leadership to align data platform development with business strategy and product goals.
• Stay at the forefront of industry trends in data engineering, lakehouse architecture, and cloud-native data platforms.

Requirements

• Strong foundation in software engineering principles, including SOLID design, modularity, and scalability.
• Expert proficiency in Databricks, including Delta Lake, Unity Catalog, Delta Live Tables, MLflow, and Databricks Workflows.
• Deep experience with Snowflake, including data modeling, performance optimization, and integration with upstream/downstream pipeline tooling.
• Expert proficiency in Python for data pipeline and automation development.
• Advanced SQL skills with experience optimizing complex queries and data models at scale.
• Proven experience designing and maintaining cloud-native data pipelines on AWS (e.g., MWAA/Airflow, Lambda, ECS, SQS, Glue, S3, Redshift, etc.).
• Experience implementing and managing Terraform or similar IaC frameworks.
• Strong understanding of lakehouse architecture patterns, data ingestion, transformation, and orchestration, including familiarity with ML/AI pipeline integration patterns.
• Familiarity with CI/CD pipelines, automated testing, and modern DevOps practices.
• 8+ years of experience in data engineering or backend development, with a focus on scalable data solutions.
• Demonstrated experience leading data infrastructure projects end-to-end and mentoring senior engineers.
• Familiarity with containerization (Docker) and workflow orchestration best practices.
• Excellent communication, collaboration, and problem-solving skills.

Nice to Have

• Experience with streaming data technologies (Kafka, Kinesis, Flink).
• Exposure to ML/AI pipeline patterns (feature stores, experiment tracking, model serving) and MLOps tooling, particularly in a cross-functional team environment.
• Experience integrating data quality and observability tools.
• Experience with Databricks as a data sharing and collaboration platform (Delta Sharing, Marketplace).
• Familiarity with Claude Code or similar AI-powered developer tools for accelerating pipeline development and code workflows.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $175,000 - $220,000

The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors.

Octus delivers breaking news and market-moving intelligence through cutting-edge data and technology for hedge funds, investment banks, and law firms- and we’re transforming how professionals access complex and opaque information. As part of our high-performing AI Innovation team, you’ll help design, build, and productionize modern GenAI and LLM-powered systems that support both client-facing features and internal operational efficiency. You’ll work end to end—from shaping ambiguous problems into scalable solutions to deploying reliable AI models in production - collaborating closely with product, engineering, and infrastructure teams. This is a hybrid role based in NYC (3 days in office per week). Curious about what we’re building? Check out our flagship GenAI product, CreditAI here and our AI framework here.

Responsibilities

• Apply strong problem-solving and critical thinking skills to break down complex, ambiguous requirements into clear, implementable technical components and system designs.
• Design, build, and maintain AI-powered and data-driven systems with a focus on modern language and multimodal models, including LLM-driven applications, RAG pipelines, and agentic workflows.
• Evaluate and productionize commercial and open-source LLMs, choosing appropriate models, tools, and techniques for each use case. Develop multi-step agentic workflows that incorporate tools, external data sources, memory, and control logic.
• Manage the orchestration of production LLM workflows and agentic systems, ensuring reliability and efficiency through prompt routing, state management, retries, fallbacks, and error handling. Design, test, and iteratively refine prompts and system instructions using prompt engineering and tuning techniques to improve model reliability, accuracy, and task performance.
• Maintain production-grade code and services with automated monitoring and performance tracking, using metrics and alerts to guide continuous improvements in models, prompts, and pipelines.
• Apply systems thinking to design and optimize AI and LLM systems, balancing quality, scalability, latency, cost, and operational complexity, while implementing efficiency improvements using model selection, prompt design, batching, caching, and retrieval strategies.
• Define and implement evaluation and observability frameworks for AI systems, including automated testing, task-specific benchmarks, regression testing for prompts, human-in-the-loop validation, and performance monitoring.
• Build and integrate AI models into backend systems and APIs to support both real-time and batch inference, ensuring solutions are production-ready, scalable, and efficient.
• Apply NLP and ML techniques to tasks such as information extraction, semantic search and retrieval, text classification, summarization, and reasoning over text and documents.
• Collaborate closely with engineering and infrastructure teams to deploy solutions using containerized and cloud-based environments (e.g., GitHub, Docker, AWS), applying modern deployment and infrastructure practices.
• Collaborate with product managers, business stakeholders, and domain experts to translate complex, ambiguous business problems into actionable technical solutions, and communicate progress, trade-offs, and outcomes to relevant stakeholders.
• Continuously learn and adapt to advancements in NLP and Generative AI to ensure solutions remain innovative and effective.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• 3+ years of experience as a Data Scientist, Machine Learning Engineer, or applied AI practitioner, with a strong foundation in computer science, algorithms, and software development. 
• Advanced programming skills in Python, with experience building production-grade systems beyond research or experimentation.
• Solid understanding of machine learning and applied AI concepts, with experience taking solutions from prototype to production.
• Hands-on experience designing, building, and deploying LLM-driven or GenAI applications, including familiarity with vector databases, embeddings pipelines, or semantic search systems.
• Practical experience with cloud-based deployments and infrastructure tools (e.g., AWS, Docker, GitHub) and an understanding of modern DevOps practices, containerization, orchestration, caching strategies, and cost-aware design.
• Strong problem-solving skills and systems thinking, with the ability to balance trade-offs across model quality, scalability, inference latency, cost, and operational complexity.
• Ability to interpret and implement research ideas and algorithms, actively contributing to research and development initiatives while translating them into production solutions.
• Excellent communication and collaboration skills, with experience working closely with product managers, engineers, and domain experts to deliver actionable technical solutions.
• Passion for learning and staying current with the rapidly evolving AI/ML landscape, including emerging best practices for GenAI applications.
• Strong ownership and initiative, with the ability to independently drive projects from problem definition to delivery, while being a team player and contributing to the overall success of the data science team.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $130,000-$145,000.

The actual compensation will be at Octus’ sole discretion and will be determined by the aforementioned and other relevant factors. This position is eligible for a performance-based annual bonus.

As a DevOps Engineer at Octus, you will play a crucial role in the development, implementation, and maintenance of the cloud infrastructure for our products. This position involves close collaboration with Application Developers, Data Engineers, SRE, Security, and IT professionals to automate and streamline operations and processes. Your contributions will be essential in ensuring the reliability, scalability, and security of our systems and applications.

Core Responsibilities:

• Design, implement, and maintain CI/CD pipelines to automate the build, test, and deployment processes.
• Effectively prioritize workload with a constant focus on increasing developer efficiency.
• Manage and optimize cloud infrastructure to ensure scalability, performance, and cost-effectiveness. Experience with AWS is a plus.
• Work closely with SRE to develop and maintain monitoring and alerting systems to ensure the health and performance of our systems and applications.
• Work closely with Security to implement and enforce security best practices across our infrastructure and applications.
• Collaborate with software developers to optimize application performance and reliability.
• Participate in the planning and execution of disaster recovery and business continuity strategies.
• Effectively communicate with stakeholders to provide updates on project statuses, issues, and recommendations.
• Participate in on-call rotation to provide system support.

Core Requirements:

• At least 5 years of experience in a DevOps role.
• At least 2+ years of experience with Terraform.
• Expert knowledge of cloud concepts and services (EC2, ECS, S3, RDS, A/ELB, EBS, VPC, Route53 or equivalent).
• Expert level knowledge of Linux. Strong scripting skills for automation and tooling.
• Ability to troubleshoot, diagnose, resolve & document RCA of incidents.
• Good knowledge of database configuration, concepts, maintenance, and troubleshooting.
• Thorough understanding of Security principles and experience in designing, implementing, monitoring proper controls.
• Extensive experience with Infrastructure-as-code & configuration management tools (Terraform, SaltStack or equivalent).
• Experience with containerization technologies such as Docker and orchestration tools like Kubernetes, ECS including managing microservices architectures.
• Knowledge of CI/CD tools such as Jenkins, Github Actions or equivalent.
• Experience with monitoring and logging tools such as Datadog, Cloud Watch or equivalent.
• Excellent communication skill, with the ability to effectively collaborate with cross-functional teams.

At Octus, we consider a range of factors in connection with compensation decisions, including experience, skills, location, and our business needs and limitations. As a result, compensation may vary within and across similar roles and positions. Please note that the salary range information below is a good faith estimate for this position and actual compensation for any individual may fall outside this range if warranted by the circumstances applicable to that individual. If we identify a role that would be suitable for a broader range of skills and experience such that we would consider hiring at multiple levels then the range listed below may reflect that breadth.

The salary range estimate for this position is $165,000 - $190,000.

The actual compensation will be at Octus' sole discretion and will be determined by the aforementioned and other relevant factors.

#LI-Hybrid

P15407_3389736

The Solutions Engineer Team

We believe Solutions Engineers at Okta are involved in all stages of the customer’s digital transformation.  Solutions Engineers are experienced in using presentations, email, phone, and social media to connect with customers virtually and in person. We are looking for great teammates who can build and deliver sales presentations and customized product demonstrations to educate Okta’s Customers (from developers to product managers to C-level executives) on best practices throughout their cloud security technology journey. 

We believe Okta’s Solutions Engineers empathize with Customers and quickly discern their true technical needs by asking detailed, clarifying questions while presenting solutions that specifically address those needs. Okta Solution Engineers have the rare combination of technical acumen and business insight; in a career where you can utilize both. As a Solutions Engineer at Okta, you will further develop each of these skills by advising a diverse set of customers on the value they will gain by using Okta’s Identity Platform.

The Solutions Engineer Opportunity

Reporting to the Senior Manager, Solutions Engineers, this Senior Solutions Engineer (Okta) will partner with Commercial Account Executives. As a Senior Solutions Engineer at Okta, you will be the technical lead in all stages of the customer lifecycle. You will focus on delivering customer value by aligning customer requirements to business results enabled by Okta solutions. You will contribute to account and opportunity strategies and, collaboratively, demonstrate the value of Okta solutions through presentations, whiteboard sessions, and proof-of-concept demonstrations.

What You’ll Do

As a Senior Solutions Engineer, you’ll be a strategic technical expert for a customer-facing sales team. You'll use your skills to:

• Work alongside the Corporate/Expansion (employee size 300-1249) sales team as the technical and domain expert of a customer-facing sales team to help Customers understand the value of Okta’s solutions
• Serve as a technical advisor: Partner with the sales team to educate customers on Okta’s identity solutions and demonstrate their value.
• Solve customer challenges: Understand customer needs and provide tailored product demonstrations to show how our solutions can solve their business problems.
• Lead technical engagements: Answer product and technical questions, and plan and deliver complex Proofs of Concept (POCs) by collaborating with other Okta engineering teams.
• Drive product and knowledge growth: Share customer feedback with our product teams to influence future enhancements and contribute to the team's knowledge by sharing best practices and reusable assets.
• Stay ahead of the curve: Keep up with competitive analysis and market differentiation to better position Okta.
• Support company events: Represent Okta at marketing events, including conferences, user groups, and trade shows.

What You’ll Bring

• Experience: 8+ years of experience in pre-sales engineering and solution selling, with a strong background in Enterprise account segments.
• Technical Acumen:
• Deep understanding of identity protocols (e.g., SAML, OIDC, OAuth, FIDO, Passkeys, SCIM, LDAP).
• Working knowledge of cloud platforms like AWS, Azure/Entra, and GCP.
• Experience with REST APIs and SDKs.
• Hands-on experience in one or more of the following: front-end web development, back-end development, scripting (Bash, PowerShell), or DevOps (Docker, Kubernetes).
• Understanding of identity-related cybersecurity topics (e.g., phishing, MFA bypass attacks, privilege escalation).
• Communication & Presentation Skills: The ability to simplify complex technical concepts and deliver compelling presentations to diverse audiences, from developers to C-level executives. You should be skilled at diagramming user journeys and complex architecture.
• Strategic Mindset: Proven skills in territory management, including building pipelines and collaborating with sales counterparts.
• Travel: Ability to travel up to 25% of the time.
• A bachelor's degree in Engineering, Computer Science, MIS, or a comparable field is preferred.

Bonus Skills (Ideally, You Have)

• Experience in the IAM space
• Hands-on knowledge of Identity Governance (IGA) or Privileged Access Management (PAM) solutions.
• Practical experience with Windows Server, Active Directory, LDAP, and Federation services.

You might also have (not mandatory):

• AI & Emerging Tech: Expertise with Agentic AI and LLM-based workflows. You understand the use cases for AI agents, both internal and external, and have familiarity with MCP servers.
• Diagramming experience for user journey flows, complex architecture diagrams, etc.

#LI-Remote

#LI-CM

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The Opportunity

Auth0’s platform is the front door for thousands of customers and millions of users. On the Platform Engineering team, we build the resilient foundations that enable customers to rely on Auth0 for always-on authentication and authorization services.

As the Senior Manager of Data Streaming Services, you will lead the evolution of our streaming data backbone across a multi-cloud footprint. You will oversee multiple engineering teams dedicated to making data streaming seamless, reliable, and high-performance. This is a "manager of managers" role requiring a blend of strategic foresight, execution rigor, and technical grit. You will set the vision for our streaming services, mentor high-performing teams, and take accountability for our service uptime guarantees.

What you’ll achieve

• Lead a world-class team of teams. Oversee data streaming infrastructure and services that power our global platform across AWS and Azure.
• Own roadmap and execution. Partner with product and stakeholder teams to define the team's strategy and prioritized roadmap.
• Drive engineering excellence. Set high standards of quality, reliability, and operational robustness, championing best practices in software development, from code reviews to observability and incident management.
• Lead an automation-first culture. Reduce operational friction and ensure infrastructure is self-healing and code-defined. Draw efficiency from AI-assisted development.
• Act as a technical leader. Lead response on incidents for services under ownership and help teams navigate complex distributed systems failures.

What you’ll bring

• Proven engineering leadership, building and leading teams of teams. Experience coaching Staff+ engineers and engineering managers.
• Strong technical and architectural acumen. Background in building scalable, distributed systems. Comfortable participating in and guiding technical discussions.
• Strong project management skills. Expertise in creating technical roadmaps, prioritizing effectively in an agile environment, and managing complex project dependencies.
• Collaborative leadership style, adapted to remote ways of working. Excellent written and verbal communication skills to build strong relationships with stakeholders and inspire others.

Bonus Points

• Experience developing data-intensive applications in a modern programming language such as go, node.js, or Java.
• Experience with databases such as PostgreSQL and MongoDB.
• Experience with distributed streaming platforms like Kafka.
• Familiarity with concepts in the IAM (Identity and Access Management) domain.
• Experience with cloud providers (AWS, Azure), container technologies such as Kubernetes and Docker, and observability tools such as Datadog.
• Experience building reliable, high-availability platforms for enterprise SaaS applications.

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