What are the responsibilities and job description for the AI Engineer position at Kaleidoscope Innovation?
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Job Specs – AI Engineering Lead
About This Role
Wells fFargo is seeking a AI engineering Lead in CIB
In This role you will
Key Responsibilities
Technical Leadership
Job Specs – AI Engineering Lead
About This Role
Wells fFargo is seeking a AI engineering Lead in CIB
In This role you will
- Lead end‑to‑end design and development of AI systems including chatbots, Retrieval Augmented Generation (RAG) platforms, autonomous agents, and workflow automation tools.
- Drive complex, multi-domain AI initiatives, ensuring technical excellence across backend services, front-end experiences, and AI model integrations.
- Architect scalable and secure, AI solutions leveraging Google, OpenAI, Anthropic, Vertex AI, and GitHub’s AI ecosystem.
- Oversee enterprise-grade deployment pipelines using OpenShift (OCP), Kubernetes, and robust CI/CD patterns to ensure reliable production delivery.
- Establish engineering best practices across Python, TypeScript, and React for modern, AI-enabled applications.
- Guide prompt engineering, skill engineering, and model evaluation approaches including guardrails, observability, red teaming, and hallucination detection.
- Lead and mentor engineering pods , providing technical direction, career development, and architectural guidance.
- Ensure systems are fully observable, monitored, and resilient, integrating fallback logic and safety controls to mitigate model and system failures.
- Partner closely with UI/UX, platform, cybersecurity, and governance teams to deliver compliant, user‑centric, and secure AI solutions at enterprise scale.
- Collaborate with business stakeholders and product owners to align AI capabilities with strategic outcomes and define delivery roadmaps.
- Ensure compliance with cybersecurity, data privacy, and model risk management standards required in regulated financial‑services environments.
- Resolve complex technical issues, escalating and troubleshooting challenges across AI pipelines, backend services, front-end apps, and infrastructure.
- Lead Agile delivery processes, driving sprint execution, backlog prioritization, risk mitigation, and cross-team coordination.
- Be well versed in emerging AI technologies, staying current with LLM advancements, evaluation techniques, vector search, and responsible AI practices.
- Collaborate and influence across all levels , including senior managers, platform teams, and cross-functional partners to advance the AI engineering strategy.
- 10 years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Expert-level proficiency in:
- Python (AI/ML, backend, orchestration)
- TypeScript and modern React frameworks
- Experience building solutions using:
- OpenAI, Anthropic, Google (Vertex AI), GitHub Copilot / GitHub ecosystem
- Hands‑on experience deploying applications using:
- OCP/OpenShift, , Kubernetes, CI/CD pipelines
- Proven ability to lead multiple engineering pods and mentor engineers across levels.
- Comfortable executing Agile methodologies across short sprint cycles.
- Strong understanding of:
- Cybersecurity controls
- Model risk management
- Compliance requirements in regulated financial-services environments
- Experience building high‑availability banking or financial applications.
- Familiarity with vector databases, embeddings, search systems (e.g., ChromaDB,, Elasticsearch, Redis Vector).
- Understanding of evaluation frameworks for LLM outputs (hallucination detection, guardrails, red‑teaming).
- Exposure to MLOps fundamentals and responsible AI concepts.
Key Responsibilities
Technical Leadership
- Lead end‑to‑end design and implementation of AI systems including chatbots, Retrieval‑Augmented Generation (RAG), autonomous agents, and workflow automation tools.
- Architect scalable, secure solutions leveraging industry‑leading AI providers (OpenAI, Anthropic, Google Vertex AI, GitHub Copilot).
- Oversee production deployment pipelines using OCP (OpenShift Container Platform) for containerization, orchestration, and runtime operations.
- Define best practices for Python, TypeScript, and React development within AI‑enabled applications.
- Manage and mentor pod teams (approx. 4 / 6 engineers each), ensuring high‑quality execution and technical rigor.
- Drive delivery roadmaps, project sequencing, and risk mitigation across multiple concurrent AI initiatives.
- Partner with UI/UX designers to build intuitive, compliant, and enterprise‑ready user experiences.
- Guide prompt engineering, skill engineering, and evaluation frameworks for AI model tuning and safety.
- Ensure all AI deployments meet enterprise security, data privacy, and regulatory compliance standards required in Corporate & Investment Banking.
- Collaborate with cybersecurity, risk, and governance teams to enforce secure coding, model‑handling, and data‑access patterns.
- Design robust observability, monitoring, and fallback strategies for AI-driven production systems.
- Work closely with product owners, business stakeholders, and platform teams to align AI capabilities with business outcomes.
- Communicate feasibility, architectural trade-offs, delivery timelines, and technical risks.
- Stay current with industry trends, emerging AI technologies, model evaluation techniques, and AI governance standards.