Nextgen AI Technical Manager-Growth&Innovation
No salary listed
Expert
Buenos Aires, Argentina
In Person
AI & Machine LearningApplied Machine Learning
About the job
Requirements
- A background in AI/ML, software engineering, data engineering, or solution architecture is required.
- Prior hands-on experience building AI/ML and generative AI solutions is required.
- Experience assessing emerging AI technologies and working with engineering teams is required.
- Eight or more years of experience in AI/ML engineering, software engineering, data engineering, solution architecture, or related technical roles is required.
- Experience evaluating emerging AI technologies, architectures, models, and frameworks for enterprise applicability is required.
- Experience working with engineering teams and providing technical guidance across prototypes, pilots, or production solutions is required.
- A strong understanding of enterprise AI constraints, including privacy, security, governance, integration, scalability, and cost, is required.
- Excellent written and verbal communication skills, including the ability to engage confidently with technical and senior stakeholders, are required.
- Relevant tools and technologies include Python, SQL, Azure OpenAI, Azure AI Foundry, OpenAI API, LangChain, LangGraph, LlamaIndex, Hugging Face, Azure AI Search, Pinecone, Weaviate, pgvector, Neo4j, GitHub, Docker, Kubernetes, MLflow, model evaluation and benchmarking tools, Teams, SharePoint, and Azure DevOps.
Responsibilities
- Maintain a strong understanding of developments across next-generation AI, including emerging models, agent architectures, frameworks, open-source technologies, infrastructure patterns, and adjacent technologies.
- Conduct hands-on technical assessments of emerging capabilities to understand their maturity, limitations, enterprise applicability, and potential areas of value.
- Distinguish meaningful technical advances from market hype and summarize their implications for the Next-Gen AI team.
- Provide technically grounded insights and recommendations to leadership on areas that may warrant further exploration.
- Review business and client challenges surfaced by account teams and assess whether emerging AI capabilities could offer a relevant or differentiated approach.
- Identify connections between evolving technology capabilities and problems where traditional or currently available approaches may be insufficient.
- Develop initial technical hypotheses for how promising capabilities could be explored through focused experiments or prototypes.
- Provide leadership with technical perspectives on feasibility, maturity, dependencies, and potential value before decisions are made to pursue an opportunity.
- Translate selected opportunities into technically meaningful experiments with clear hypotheses and evaluation criteria.
- Recommend appropriate models, architectures, frameworks, data approaches, and technology components for experimentation.
- Work closely with engineering teams to provide technical direction, review proposed approaches, and challenge design decisions where appropriate.
- Identify technical risks, constraints, and trade-offs early and recommend practical alternatives.
- Define approaches to evaluate experiments across capability, accuracy, reliability, performance, cost, security, and enterprise readiness.
- Analyze experiment outcomes and determine what the results indicate about the underlying technology and its applicability.
- Capture technical learnings, reusable patterns, and limitations to inform future experimentation across the portfolio.
- Provide evidence-based recommendations to leadership on whether a capability should be explored further, refined, monitored, or deprioritized.
- Engage with engineers, technology partners, startups, open-source communities, and EY technical specialists to remain close to emerging developments.
- Assess technology and alliance capabilities from a technical perspective and identify where external expertise or platforms could accelerate experimentation.
- Connect relevant technical expertise into experiments when specialist capabilities are required.
- Examine new AI methods and delivery patterns to determine where they are feasible, responsible, and worth piloting.
- Apply governance, security, and compliance requirements consistently across the experiment-to-delivery lifecycle, ensuring alignment with EY processes.
- Use evidence and outcome signals to make timely trade-offs, reprioritize work, and steer teams toward the highest-impact results in a fast-moving environment.
About the company
EY is a global professional services firm that offers consulting, assurance (audits), tax, and transaction advisory services to a wide range of clients including corporations, SMEs, and government entities. It earns fees for these services and uses its industry expertise and a worldwide network to help clients optimize operations, manage risk, and achieve sustainable growth. EY differentiates itself through its scale and reach, industry specialization, focus on end-to-end services, strategic alliances, and emphasis on innovation and sustainability, including improving audit quality and addressing digital economy needs and supply chain visibility. The company’s goal is to help clients navigate complex regulatory and business environments, transform finance and tax functions, and drive efficiency and resilience across their operations.
Company Size
1,001-5,000
Company Stage
N/A
Total Funding
N/A
Headquarters
London, United Kingdom
Founded
1991
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Simplify's Take
What believers are saying
- EY.ai Agentic for Sales launched March 2, 2026 with Snowflake and Canva.
- EY uses client-zero deployments, scaling Copilot across 400,000 people by May 2026.
- EY’s 2026 AI assurance push monetizes client demand for governance, controls, and risk reviews.
What critics are saying
- Sabah filed RM2.4 billion audit-negligence claims against EY on July 30, 2026.
- EY set aside £188 million in March 2026 after NMC, Shell, and Made.com scrutiny.
- Repeated audit failures can destroy trust, trigger client defections, and shrink the franchise permanently.
What makes Ernst & Young unique
- EY Canvas processes 1.4 trillion journal-entry lines across 160,000 global audits.
- EY-Microsoft invested US$1b+ in May 2026 to industrialize enterprise AI delivery.
- EY launched agentic audit AI on April 7, 2026, spanning Assurance and AI assurance.
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Benefits
- Professional Development Budget
- Flexible Work Hours
- Remote Work Options