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We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

We are looking for a dynamic and technically proficient Software Engineering Director to lead the development of our Generative AI (GenAI) platform, which focuses on Agentic workflows and Retrieval-Augmented Generation (RAG) systems. This is a great opportunity to work on next-generation AI products that integrate large-scale language models, sophisticated retrieval systems, and AI agent frameworks! As the Software Engineering Director, you will lead a team of engineers to build, scale, and optimize an AI-driven platform, while fostering a culture of innovation and technical excellence.

Key Responsibilities:
Team Leadership & People Management

• Lead a talented team of software engineers to build and maintain AI systems that support Agentic and RAG workflows.
• Mentor engineers, providing technical guidance and fostering professional growth with a passion for team and team members’ success.
• Attract, hire, and retain top-tier engineering talent while promoting an environment of collaboration, continuous learning, and high performance.
• Conduct regular performance evaluations, offer continuous feedback, and support the professional development of team members.
• Guide your team in exploring new technologies, models, and approaches that enhance the Agentic and RAG capabilities of the platform.

Engineering Management:

• Collaborate with product managers, data scientists, and AI researchers to define the product roadmap and align technical initiatives with business objectives.
• Drive the development and deployment of AI features and architecture, ensuring that they are well-integrated into the product and contribute to customer value.
• Lead the development of prototypes and rapid experimentation to evaluate new algorithms, models, or approaches, balancing time-to-market with long-term technical investments.
• Own project delivery timelines, ensuring that engineering deliverables are met while managing the balance between technical debt, proactive risk mitigation, and product innovation.
• Occasionally chipping in to development tasks such as coding and feature verifications to assist teams with release commitments, to gain an understanding of the deeply technical product as well as to keep your technical skill sharp.

Operational Excellence & Best Practices:

• Ensure the team follows best practices in software development, including CI/CD, automated testing, version control, and deployment pipelines.
• Establish monitoring and logging infrastructure to ensure the system is highly observable, enabling efficient debugging and diagnosis of issues in AI Agentic workflows.
• Daily management of stand-ups as the Scrum Master for engineering teams as well as ensuring the team has clear, understandable priorities and can lead multi-functional handoff discussions.
• Implement frameworks and tools to track the performance and accuracy of AI models, including those used in RAG systems.

Stakeholder Communication & Collaboration:

• Drive the execution and delivery of features by collaborating with many multi-functional teams, architects, product owners, researchers, engineers, and customer success teams.
• Clearly communicate the technical challenges, progress, and achievements of the engineering team to non-technical stakeholders.
• Work closely with the leadership team to influence and shape the strategic direction of the product from a technical standpoint.

Required Skills & Qualifications:
Technical Leadership

• Strong technical expertise in Generative AI, particularly with RAG systems and Agentic workflows that use large language models.
• Proven ability to design and architect complex, high-performance systems that support AI workloads.

People Management:

• Demonstrated experience in managing and growing impactful engineering teams in fast-paced environments.
• Excellent communication and leadership skills, with the ability to inspire and motivate a team.
• A proven track record of successfully mentoring engineers and fostering their career development.

AI & Machine Learning Expertise:

• Strong understanding of AI and machine learning concepts, including experience with LLMs, retrieval-augmented generation, and agent-based systems.
• Familiarity with the ML lifecycle, including model training, deployment, inferencing, and the challenges associated with scaling AI products.
• Experience working with AI-related infrastructure on cloud platforms (e.g., AWS, GCP, Azure) and managing the complexities of large-scale data pipelines and inferencing systems.

Startup Mentality:

• Thrive in a fast-moving startup environment with constantly evolving priorities and tight deadlines.
• Strong sense of ownership, with a bias for action and a focus on delivering results quickly and efficiently.
• Willingness to be hands-on when necessary, making technical contributions alongside the engineering team.

Benefits & Perks
Check out our benefits site which explains our various benefits, including wellbeing reimbursement, generous parental leave, adoption assistance, fertility benefits, and more.

Salesforce Information
Check out our Salesforce Engineering Site.

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