{"id":1726504,"url":"https://alion.io/job/factset-ffr-lead-software-engineer-backend-aiml-cloud","title":"FFR - Lead Software Engineer – Backend & AI/ML & Cloud","company":{"id":2786132,"name":"Workday","domain":"myworkdayjobs-impl.com","url":"https://alion.io/company/myworkdayjobs-impl","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":99,"open_postings":63,"ghost_share":0,"stale_share":0.032,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":62000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":44},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Amazon ECS","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Fargate","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Django","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Hugging Face","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"LLM","optional":false},{"name":"Mistral","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"Transformers","optional":false},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"ETL/ELT","optional":true},{"name":"IAM","optional":true},{"name":"MLFlow","optional":true},{"name":"Plotly","optional":true},{"name":"pySpark","optional":true},{"name":"Spark","optional":true},{"name":"Streamlit","optional":true}],"status":"live","first_seen_at":"2026-09-15T00:00:00Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-10-20T16:33:56Z","board_verified":true,"closed_at":null,"days_open":35,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":35},"description":"FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.\nAt FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big rolein how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipatingour clients’ needs and exceeding their expectations.\nYour Team's Impact\nThe team comprises highly motivated engineers and stakeholders who are passionate about extracting targeted insights from diverse document sources and transforming them into high-value data products. Leveraging cutting-edge technologies, the team focuses on building scalable pipelines that efficiently collect, structure, and process large volumes of data.\nOver time, the team has developed a robust and high-performing data pipeline capable of generating best-in-class structured datasets that power FactSet’s products. Currently, the team is advancing this ecosystem by driving end-to-end automation across multiple stages of the pipeline. This includes the development of an event-driven, GenAI-centric, agent-based infrastructure aimed at enhancing efficiency, scalability, and innovation in data processing workflows.\nSUB-PROCESS BRIEF\nLeads development strategies, architecture designs, data management, and code flow analysis necessary for the software development life cycle. Works closely with different groups/teams to ensure engineering team delivers on precision/correctness,performance, and scalability across our distributed computational framework.\nWhat You'll Do:-\nAI/ML & LLM Expertise:\nDesign, fine-tune, and deploy small and open-source large language models (LLMs) such as Llama, Mistral, OpenAI GPT, etc.\n\nHands-on leadership in prompt engineering, few-shot prompting, and building advanced NLP/NLU workflows.\n\nGuide adoption of modern AI/ML frameworks (Hugging Face Transformers, LangChain, LangGraph, etc.) and architect reusable pipelines in Python.\n\nPython & API Development:\nDrive critical systems architecture in Python, using best practices in API and microservices design (FastAPI, Flask, Django, etc.).\n\nCloud Deployment (AWS/Azure/GCP):\nArchitect, deploy, and scale robust, production-grade ML/AI solutions on cloud (AWS strongly preferred), leveraging cloud-native tools (Lambda, S3, ECS/ECR/Fargate, etc.), serverless, and IaC (CloudFormation/Terraform).\n\nChampion DevOps best practices, automation, containerization (Docker/K8s), CI/CD, and operational monitoring.\n\nTechnical Leadership:\nMentor engineers, lead by example, drive system architecture reviews and code standards, and ensure high-quality technical delivery across teams.\n\nAct as the technical point of contact for escalation, incident resolution, and production troubleshooting.\n\nWhat We're Looking For:-\nExperience:\n8-12 years in software development, including 3+ in senior or lead roles delivering ML/AI solutions in a cloud environment.\n\nLLM & Prompt Engineering:\nStrong real-world experience in LLM prompt engineering, few-shot prompting, and fine-tuning (using frameworks like Hugging Face, LangChain, LangGraph, etc.).\n\nPython Expertise:\nMastery of Python for API/microservice development, object-oriented patterns, code optimization, automated testing, and packaging.\n\nCloud (AWS Preferred):\nHands-on deployment and scaling of AI/ML services on AWS, Azure, or GCP; proficient in containers, serverless, and infrastructure as code.\n\nTechnical Leadership:\nProven experience mentoring software engineers, shaping system design, and driving cross-team initiatives.\n\nCommunication:\nExceptional ability to explain complex technical subjects and influence technical direction with diverse audiences.\n\nNice to Have:-\nDatabricks:\nExperience building, deploying, or orchestrating ML/AI or data pipelines on Databricks (Data Engineering, MLflow, collaborative workflows, jobs).\n\n(Note: Knowledge of Databricks is highly valued but not required; candidates without PySpark but with Databricks experience are welcome.)\n\nPySpark:\nExperience using PySpark for big data ETL/processing, but not a must-have.\n\nData Engineering:\nFamiliarity with Spark, Airflow, advanced data analytics stacks, and modern data lakes (e.g., Delta Lake).\n\nML Productionization & MLOps:\nExperience with ML lifecycle tools, CI/CD pipelines, monitoring, and model governance.\n\nVisualization:\nPython-based dashboarding/analytics (Streamlit, Dash, Plotly).\n\nSecurity & Compliance:\nSecure cloud design, IAM, encryption, and compliance frameworks.\n\nPublished Work / Open Source:\nContributions to AI/ML communities, conference presentations, or technical publications.\n\nQualifications\nBachelor's degree in Engineering, Computer Science, or equivalent.\n\nExperience working in product engineering organizations preferred.\n\nWhat's In It For You\nAt FactSet, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a FactSetter means:\nThe opportunity to join an S&P 500 company with over 45 years of sustainable growth powered by the entrepreneurial spirit of a start-up.\n\nSupport for your total well-being. This includes health, life, and disability insurance, as well as retirement savings plans and a discounted employee stock purchase program, plus paid time off for holidays, family leave, and company-wide wellness days.\n\nFlexible work accommodations. We value work/life harmony and offer our employees a range of accommodations to help them achieve success both at work and in their personal lives.\n\nA global community dedicated to volunteerismand sustainability, where collaboration is always encouraged, and individuality drives solutions.\n\nCareer progression planning with dedicated time each month for learning and development.\n\nBusiness Resource Groups open to all employees that serve as a catalyst for connection, growth, and belonging.\n\nLearn more about our benefits here.\nSalary is just one component of our compensation package and is based on several factors including but not limited to education, work experience, and certifications.\nCompany Overview:\nFactSet (NYSE:FDS| NASDAQ:FDS) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees’ Choice Award winner. Learn more at www.factset.com and follow us on X and LinkedIn.\nAt FactSet, we celebrate difference of thought, experience, and perspective. 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