Freddie Mac
Agile Development Sr Tech Lead (Gen AI Data Scientist)
Freddie Mac, Mc Lean, Virginia, us, 22107
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Agile Development Sr Tech Lead (Gen AI Data Scientist)
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Freddie Mac 1 week ago Be among the first 25 applicants Join to apply for the
Agile Development Sr Tech Lead (Gen AI Data Scientist)
role at
Freddie Mac At Freddie Mac, our mission of Making Home Possible is what motivates us, and its at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview
As the
Agile Dev Lead Sr Tech Lead (Gen AI Scientist) , you will lead the design and development of advanced Generative AI solutions, including AI Agents, Agentic Workflows, and Gen AI Applications that tackle complex business challenges. This hands?on role demands deep expertise in LLMs, multi?modal AI, prompt engineering, and cloud?native GenAI (CI/CD) deployments, as well as the ability to shape and implement enterprise?grade Gen AI systems as both a technical thought leader. Our Impact Enable the organization to automate and enhance decision?making processes. Accelerate innovation through intelligent data?driven applications. Establish best practices for deploying AI safely and ethically at enterprise scale. Foster a culture of collaboration, technical excellence, and continuous learning.
Your Impact
Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications to address diverse and complex business use cases. Develop, fine?tune, and optimize lightweight LLMs; lead the evaluation and adaptation of models such as Claude (Anthropic), Azure OpenAI, and open?source alternatives. Design and deploy Retrieval?Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases. Curate enterprise data using connectors integrated with AWS Bedrocks Knowledge Base/Elastic. Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent?to?Agent) communication. Build and maintain Jupyter?based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS). Deploy MCP services using CI/CD pipelines (GenAI Ops). Collaborate with cross?functional teams of UI and microservice engineers, designers, and data engineers to build full?stack Gen AI experiences. Integrate GenAI solutions with enterprise platforms via API?based methods and GenAI standardised patterns. Establish and enforce validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails for production?ready deployment. Design and build robust ingestion pipelines that extract, chunk, enrich, and anonymise data from PDFs, video, and audio sources for use in LLM?powered workflowsleveraging best practices like semantic chunking and privacy controls. Orchestrate multimodal pipelines using scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows appropriate for unstructured media. Implement embedding drivesmap media content to vector representations using embedding models, and integrate with vector stores (AWS KnowledgeBase/Elastic/Mongo Atlas) to support RAG architectures.
Qualifications
Bachelor of science and/or Masters of science with advanced studies in AI/Data Science. 10+ years of experience in AI/ML, with 3+ years in applied GenAI or LLM?based solutions. Deep expertise in prompt engineering, fine?tuning, RAG, GraphRAG, vector databases (e.g., AWS KnowledgeBase / Elastic), and multimodal models. Proven experience with cloud?native AI development (AWS SageMaker, Bedrock, MLFlow on EKS). Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.). Deep understanding of Gen AI system patterns and architectural best practices, Evaluation Frameworks. Demonstrated ability to work in cross?functional agile teams.
Keys to Success in this Role
Demonstrate Deep Technical Mastery
Advanced proficiency in GenAI concepts, LLMs, multimodal AI, and cloud?native ML workflows. Architect Scalable and Robust Solutions
Ability to design and deploy AI systems that are secure, scalable, and maintainable; expertise in building RAG architectures, data ingestion pipelines, and embedding?driven retrieval systems. Collaborate Across Functions
Work effectively with developers, designers, product managers, and data engineers; communicate complex technical ideas clearly and lead teams towards shared goals. Champion Best Practices and Safety
Implement rigorous validation and evaluation frameworks; establish guardrails for bias mitigation, safety, and privacy. Innovate Continuously
Stay abreast of the latest GenAI research and technologies; proactively identify opportunities for impact and improvement.
Additional Information
Current Freddie Mac employees please apply through the internal career site. We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. A safe and secure environment is critical to Freddie Macs business. This includes employee commitment to our acceptable use policy, applying a vigilance?first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs. Notice: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act. Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. Seniority Level
Mid?Senior level Employment Type
Full?time Job Function
Engineering and Information Technology #J-18808-Ljbffr
Agile Development Sr Tech Lead (Gen AI Data Scientist)
role at
Freddie Mac 1 week ago Be among the first 25 applicants Join to apply for the
Agile Development Sr Tech Lead (Gen AI Data Scientist)
role at
Freddie Mac At Freddie Mac, our mission of Making Home Possible is what motivates us, and its at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview
As the
Agile Dev Lead Sr Tech Lead (Gen AI Scientist) , you will lead the design and development of advanced Generative AI solutions, including AI Agents, Agentic Workflows, and Gen AI Applications that tackle complex business challenges. This hands?on role demands deep expertise in LLMs, multi?modal AI, prompt engineering, and cloud?native GenAI (CI/CD) deployments, as well as the ability to shape and implement enterprise?grade Gen AI systems as both a technical thought leader. Our Impact Enable the organization to automate and enhance decision?making processes. Accelerate innovation through intelligent data?driven applications. Establish best practices for deploying AI safely and ethically at enterprise scale. Foster a culture of collaboration, technical excellence, and continuous learning.
Your Impact
Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications to address diverse and complex business use cases. Develop, fine?tune, and optimize lightweight LLMs; lead the evaluation and adaptation of models such as Claude (Anthropic), Azure OpenAI, and open?source alternatives. Design and deploy Retrieval?Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases. Curate enterprise data using connectors integrated with AWS Bedrocks Knowledge Base/Elastic. Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent?to?Agent) communication. Build and maintain Jupyter?based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS). Deploy MCP services using CI/CD pipelines (GenAI Ops). Collaborate with cross?functional teams of UI and microservice engineers, designers, and data engineers to build full?stack Gen AI experiences. Integrate GenAI solutions with enterprise platforms via API?based methods and GenAI standardised patterns. Establish and enforce validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails for production?ready deployment. Design and build robust ingestion pipelines that extract, chunk, enrich, and anonymise data from PDFs, video, and audio sources for use in LLM?powered workflowsleveraging best practices like semantic chunking and privacy controls. Orchestrate multimodal pipelines using scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows appropriate for unstructured media. Implement embedding drivesmap media content to vector representations using embedding models, and integrate with vector stores (AWS KnowledgeBase/Elastic/Mongo Atlas) to support RAG architectures.
Qualifications
Bachelor of science and/or Masters of science with advanced studies in AI/Data Science. 10+ years of experience in AI/ML, with 3+ years in applied GenAI or LLM?based solutions. Deep expertise in prompt engineering, fine?tuning, RAG, GraphRAG, vector databases (e.g., AWS KnowledgeBase / Elastic), and multimodal models. Proven experience with cloud?native AI development (AWS SageMaker, Bedrock, MLFlow on EKS). Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.). Deep understanding of Gen AI system patterns and architectural best practices, Evaluation Frameworks. Demonstrated ability to work in cross?functional agile teams.
Keys to Success in this Role
Demonstrate Deep Technical Mastery
Advanced proficiency in GenAI concepts, LLMs, multimodal AI, and cloud?native ML workflows. Architect Scalable and Robust Solutions
Ability to design and deploy AI systems that are secure, scalable, and maintainable; expertise in building RAG architectures, data ingestion pipelines, and embedding?driven retrieval systems. Collaborate Across Functions
Work effectively with developers, designers, product managers, and data engineers; communicate complex technical ideas clearly and lead teams towards shared goals. Champion Best Practices and Safety
Implement rigorous validation and evaluation frameworks; establish guardrails for bias mitigation, safety, and privacy. Innovate Continuously
Stay abreast of the latest GenAI research and technologies; proactively identify opportunities for impact and improvement.
Additional Information
Current Freddie Mac employees please apply through the internal career site. We consider all applicants for all positions without regard to gender, race, color, religion, national origin, age, marital status, veteran status, sexual orientation, gender identity/expression, physical and mental disability, pregnancy, ethnicity, genetic information or any other protected categories under applicable federal, state or local laws. We will ensure that individuals are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. A safe and secure environment is critical to Freddie Macs business. This includes employee commitment to our acceptable use policy, applying a vigilance?first approach to work, supporting regulatory mandates, and using best practices to protect Freddie Mac from potential threats and risk. Employees exercise this responsibility by executing against policies and procedures and adhering to privacy & security obligations as required via training programs. Notice: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act. Notice to External Search Firms: Freddie Mac partners with BountyJobs for contingency search business through outside firms. Resumes received outside the BountyJobs system will be considered unsolicited and Freddie Mac will not be obligated to pay a placement fee. Seniority Level
Mid?Senior level Employment Type
Full?time Job Function
Engineering and Information Technology #J-18808-Ljbffr