Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A leading global professional services organization is helping enterprises accelerate AI adoption by delivering enterprise-scale Generative AI solutions. Through a combination of advanced engineering, industry expertise, and collaborative delivery models, the organization partners with clients to design, deploy, and scale AI-powered platforms that transform mission-critical business operations. Engineering teams work closely with client stakeholders to deliver innovative, production-ready solutions across cloud, data, and AI ecosystems.
Key Responsibilities
- Lead forward-deployed engineering pods delivering enterprise-scale AI and Generative AI solutions.
- Serve as the primary engineering advisor to client executives, product leaders, and technical stakeholders.
- Define technical strategy, success metrics, and phased delivery plans from prototype through production deployment.
- Translate complex engineering trade-offs into clear recommendations for executive decision-makers.
- Represent the engineering organization during client engagements, solution demonstrations, and strategic initiatives.
- Lead engineering teams consisting of onshore and offshore resources while ensuring successful project execution.
- Establish delivery standards, sprint planning, stakeholder communication, risk management, and quality assurance processes.
- Coordinate multiple engineering workstreams while maintaining architectural consistency and delivery excellence.
- Mentor and develop engineers through technical coaching and leadership.
- Architect and oversee the development of LLM-powered applications, AI assistants, agentic workflows, copilots, and enterprise knowledge search solutions.
- Guide prompt engineering strategies, tool integration, and human-in-the-loop AI workflows.
- Design and govern Retrieval-Augmented Generation (RAG) pipelines, including data ingestion, embedding, vector search, chunking, and hybrid retrieval strategies.
- Define AI evaluation frameworks covering quality, safety, latency, hallucination risks, governance, and operational performance.
- Review production-quality code and provide technical guidance on software engineering best practices.
- Guide the design and implementation of scalable data pipelines supporting AI-powered applications.
- Promote engineering excellence through CI/CD, testing, documentation, monitoring, logging, version control, and secure software development practices.
- Provide technical leadership across cloud environments, including AWS, Microsoft Azure, and Google Cloud Platform.
Required Qualifications
- Bachelor’s degree or equivalent in Computer Science, Data Science, Engineering, or a related technical discipline.
- 7+ years of experience in software engineering, data engineering, analytics engineering, or data science.
- 1+ years of hands-on experience designing and deploying Generative AI or LLM-powered applications in production environments.
- 1+ years of experience working with Palantir platforms, including Foundry, AIP, or Maven.
- Experience leading technical engagements and translating business requirements into AI-powered solutions.
- Experience developing reliable, maintainable, and well-documented software.
- Strong client communication and stakeholder management skills.
- Ability to travel approximately 50% based on project and client requirements.
Preferred Qualifications
- Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
- Experience collaborating directly with enterprise technical teams and business stakeholders.
- Background in data engineering technologies such as Spark, Airflow, dbt, streaming platforms, or machine learning pipelines.
- Experience implementing MLOps or LLMOps practices, including model evaluation, monitoring, and prompt management.
- Experience integrating LLM applications with enterprise systems through APIs, microservices, or event-driven architectures.
- Experience leading hybrid onshore/offshore engineering teams.
- Familiarity with enterprise security, privacy, governance, and regulatory compliance practices.
Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals globally.
- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
- To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
- No Liability: SpringCube is not liable for inaccuracies.
