Feature Lead - Technology, AI​/ML

Job Overview

Lead position in Bank of America’s Erica, Chat, and Voice Technology organization. The team builds next‑generation AI and Search platforms to enable virtual financial assistant/AI and search capabilities across multiple channels.

• Design, develop and be accountable for feature delivery, applying enterprise standards for solution design, coding, and quality.
• Ensure solutions meet product acceptance criteria with minimal technical debt.
• Guide the team on work breakdown and execution.
• Work with the Product Owner to keep the product backlog healthy, with clear acceptance criteria.
• Play a team‑lead role as an individual contributor and mentor the team.
• Guide team members with skills and practices, including planning and estimation, peer reviews, and other engineering practices.
• Guide the team on solution design, AI/ML model integration, work breakdown, and execution.
• Evaluate and apply emerging AI technologies, frameworks, and models to solve business problems.
• Lead the deployment and optimization of AI workloads across CPU/GPU infrastructures and cloud platforms.
• Ensure AI solutions meet enterprise standards for security, governance, observability, performance, and responsible AI practices.
• Guide the team in implementing prompt engineering, retrieval strategies, model evaluation, and inference optimization techniques.
• Drive technical innovation and adoption of AI/ML best practices across the organization.

• 5+ years of hands‑on software development experience using Java, Python, or related technologies.
• Strong software engineering skills with proficiency in Python and Java.
• Experience building AI/ML‑powered applications using machine learning and generative AI techniques.
• Knowledge of modern AI technologies including Transformers, large language models, Agentic AI, and generative AI frameworks.
• Experience implementing Retrieval Augmented Generation pipelines and related retrieval techniques.
• Experience deploying and optimizing AI applications on CPU/GPU infrastructure using technologies such as CUDA, vLLM, Triton, or equivalent inference platforms.
• Understanding of supervised, unsupervised, and reinforcement learning methodologies.
• Good understanding of source control systems such as Git and modern collaborative development practices.
• Good interpersonal communication skills for technical and business conversations.
• Good analytical skills to break down requirements and solve complex problems.
• Proven task management and leadership skills.
• Experience building restful web services.

• Experience in performance tuning with understanding of JVM internals.
• Experience with No
  
  SQL databases like Cassandra.
• Experience in distributed caching frameworks such as Hazelcast, Ignite, Redis.
• Experience in modern JVM languages like Groovy, Scala.
• Experience with full‑stack development, especially including Angular.
• Experience with generative AI Spring MVC.
• Experience with container technologies, such as Kubernetes and Docker.
• Experience with NLP and machine learning.
• Prior open‑source contributions.
• Background in mathematics or statistics.
• Experience working in agile teams.
• Experience building chatbot, conversational AI, or virtual assistant platforms.
• Experience with Azure, AWS, or cloud‑native AI platforms.
• Experience with vector databases, embeddings, semantic search, and AI retrieval systems.
• Experience with Elasticsearch, Solr, Open Search, or related search technologies.
• Experience with MLOps, model deployment, monitoring, and AI observability.
• Experience with inference optimization frameworks, GPU acceleration, and distributed model serving.
• Experience with prompt engineering, model evaluation, and AI safety/governance practices.

• Automation
• Influence
• Result Orientation
• Stakeholder Management
• Technical Strategy Development
• Architecture
• Business Acumen
• Risk Management
• Solution Delivery
• Process
• Solution Design
• Agile Practices
• Analytical Thinking
• Collaboration
• Data Management
• Dev Ops Practices

Bachelor’s or Master’s Degree in Computer Science or related field.

Shift: 1st shift (United States of America).

Hours per week: 40.

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