{"id":22415,"url":"https://alion.io/job/point72-data-engineer-investment-services","title":"Data Engineer, Investment Services","company":{"id":3801,"name":"Point72","domain":"point72.com","url":"https://alion.io/company/point72","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":true,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":79,"open_postings":176,"ghost_share":0.273,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":138,"computed_at":"2026-10-20T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Warsaw, Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":93000,"max_usd":153000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":108},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Edge AI","optional":false},{"name":"Embeddings","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2025-08-29T11:01:14Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-10-20T20:27:49Z","board_verified":true,"closed_at":null,"days_open":417,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":416},"description":"A Career with Point72's AI/ML - Investment Services Team\nThe AI/ML - Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning.\nWHAT YOU'LL DO\nDesign and build scalable, high-performance backend systems that power investment services and AI-driven applications, and own their end-to-end lifecycle\nBuild and operate robust data pipelines for batch and streaming workloads to ingest, transform, validate, and deliver data to models and downstream consumers\nIntegrate and productionize generative AI capabilities and large language model solutions, including model serving, embeddings, and API-based workflows to augment investment workflows\nImplement and maintain microservices and APIs that expose data and model functionality with a focus on reliability, low latency, and security\nOptimize system performance and resilience through monitoring, observability, capacity planning, and automated incident response\nLead cross-functional delivery of prototypes into production by collaborating with data scientists, researchers, product owners, and operations teams\nBuild and maintain CI/CD pipelines, automated testing, and deployment practices to accelerate safe delivery and rollback of services\nMentor and coach engineers on backend and data engineering best practices, help grow engineering capability, and contribute to the technical roadmap\nCollaborate with security, compliance, and infrastructure partners to ensure data governance, access controls, and operational controls are integrated into solutions\nWHAT'S REQUIRED\nBachelor's degree in computer science, software engineering, or a related technical field\nAt least 5 years of professional software engineering experience with a focus on backend system engineering\nExperience building production data pipelines or data engineering solutions for batch and streaming data\nDemonstrated experience developing or integrating generative AI and large language model solutions, such as model serving, embedding pipelines, fine-tuning workflows, or production integration with model APIs\nStrong programming skills in one or more backend languages such as Java, Python, or Go, with demonstrated ability to design maintainable code and services\nExperience deploying and operating services on cloud platforms and container platforms using Docker and container orchestration technologies\nProven experience building CI/CD pipelines, automated testing, and infrastructure-as-code for service deployments\nStrong data skills including SQL, data modeling, and experience with both relational and non-relational data stores\nExcellent verbal and written communication skills in English and demonstrated ability to collaborate with technical and non-technical stakeholders\nCommitment to the highest ethical standards\nWE TAKE CARE OF OUR PEOPLE\nWe invest in our people, their careers, their health, and their well-being. When you work here, we provide:\nSports card\nPrivate life insurance\nPrivate medical and dental care, with vision allowance\nPrivate pension scheme\nVolunteer opportunities\nSupport for employee-led affinity groups representing women, people of color and the LGBT+ community\nBusiness travel accident insurance\nEmployee assistance program\nEducational assistance reimbursement\nABOUT POINT72\nPoint72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry's brightest talent by cultivating an investor-led culture and committing to our people's long-term growth. For more information, visit https://point72.com/.\nOur Warsaw office gives us access to world-class talent with a reputation for excellence and innovation. We're looking to build an office of subject-matter experts whose fresh perspectives will help evolve our infrastructure and advance the capabilities of our teams. 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