lead ai engineer

Equifax

<div>What you&rsquo;ll do
As our Lead AI Engineer, you will be the driving force behind our technical vision and execution. Your core responsibilities include:
<ul><li>Implement Sophisticated AI Agents: Design, build, and deploy complex AI agents using LangChain and LangGraph. You will own the core logic that automates intricate decision-making within the claims lifecycle.
</li><li>Master Prompt &amp; Context Engineering: Design, test, and refine complex prompts and contextual data frameworks to ensure our AI agents perform with maximum accuracy, efficiency, and reliability.
</li><li>Lead AI Research &amp; Innovation: Stay at the bleeding edge of AI. You&rsquo;ll be responsible for identifying, prototyping, and integrating the latest foundational models, RAG techniques, and agentic frameworks to solve unique business challenges.
</li><li>Build for Production Scale on GCP: Engineer and operate our AI systems in a scalable, reliable production environment on Google Cloud Platform. Your work will directly impact millions of users.
</li><li>Champion MLOps for Agentic Systems: Establish and lead best practices for the reliability, versioning, monitoring, and observability of our AI agents, using tools like Langfuse to ensure production-grade performance.
</li><li>Collaborate to Deliver Impact: Partner closely with product leaders, data scientists, and other engineers to translate business needs into technical reality, ensuring our AI solutions are both innovative and effective.
</li><li>Champion modern software development practices by actively using AI code-assist tools (e.g., Gemini code assists, Github Copilot, Claude code) to accelerate development cycles, generate documentation, improve code quality, testing, and monitoring &amp; observability practices
</li><li>Build, manage, and mentor a cross-functional team of software, quality, and reliability engineers, fostering a culture of technical excellence and continuous improvement.
</li><li>Define and report on key engineering metrics (SLA, SLO, SLI) and ensure compliance with security, quality, and financial operations (DevSecOps, FinOps) best practices.
</li><li>Collaborate with product managers, architects, SREs and business partners to define technical strategy, create software roadmaps, and make key architectural and design decisions.
</li><li>Lead troubleshooting efforts to resolve production and customer issues, demonstrating deep technical expertise and problem-solving skills.
</li><li>Participate and lead agile team activities, including Sprint Planning and Retrospectives, to ensure efficient and predictable delivery
</li><li>Lead with a data/metrics driven mindset with a extreme focus towards optimizing and creating efficient solutions
</li><li>Drive up-to-date technical documentation including support, end user documentation and run books
</li><li>Create and deliver technical presentations to internal and external technical and non-technical stakeholders communicating with clarity and precision, and present complex information in a concise format that is audience appropriate
</li></ul>What You'll Bring (Experience &amp; Technical Stack)
<ul><li>Bachelor's degree or equivalent experience
</li><li>7+ years in software engineering, with a strong track record of technical leadership and shipping complex, scalable systems.
</li><li>2+ years in a dedicated AI/ML role, with hands-on experience in model integration, MLOps, and applying AI to solve business problems.
</li><li>1+ years of direct experience architecting and building solutions with LangChain, LangGraph, or similar agentic AI frameworks.
</li><li>2+ years of in-depth experience with Google Cloud Platform (GCP), specifically its AI/ML services (Vertex AI, etc.).
</li><li>3+ years of proven experience leveraging Kubernetes workloads.
</li><li>Proficiency in Python, JavaScript/TypeScript and/or Java and working knowledge of a modern front-end framework (Angular, React, or Vue) to collaborate effectively with UI teams.
</li><li>Hands-on experience with LLM observability tools like Langfuse for monitoring and debugging agentic workflows
</li><li>Cloud-Native Proficiency:
<ul><li>Cloud Platforms: Extensive hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure).
</li><li>Containerization: Mastery of Docker for containerizing applications and Kubernetes for orchestration.
</li><li>Infrastructure as Code (IaC): Proficiency with tools like Terraform or CloudFormation to manage infrastructure programmatically.
</li><li>CI/CD Tools: Experience with CI/CD tools such as Github Actions, Argo CD, Jenkins
</li><li>Database Knowledge: Strong experience with both SQL (e.g., Spanned DB, Alloy DB, PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, DynamoDB and Firestore) databases.
</li><li>Cloud-Native Proficiency:
</li><li>Cloud Platforms: Extensive hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure).
</li><li>Containerization: Mastery of Docker for containerizing applications and Kubernetes for orchestration.
</li><li>Infrastructure as Code (IaC): Proficiency with tools like Terraform or CloudFormation to manage infrastructure programmatically.
</li><li>CI/CD Tools: Experience with CI/CD tools such as Github Actions, Argo CD, Jenkins
</li><li>Database Knowledge: Strong experience with both SQL (e.g., Spanned DB, Alloy DB, PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, DynamoDB and Firestore) databases. 
</li></ul></li></ul>What could set you apart
<ul><li>Strong expertise in Generative AI (GenAI), including hands-on experience with models like Gemini, ChatGPT, Claude, or Llama.
</li><li>You are adept at leveraging modern development tools, including AI-powered code assistants (like GitHub Copilot), to accelerate the development lifecycle and rapidly ship high-quality features
</li><li>Experience creating and deploying AI agents to production environments.
</li><li>You have a history of tackling ambiguous, complex technical challenges and architecting elegant, effective solutions.
</li><li>You are passionate about the potential of AI, but you are grounded in the practical realities of building and shipping reliable, production-ready software.
</li><li>You thrive in a team-oriented environment, capable of mentoring other engineers and clearly communicating complex technical ideas to any audience.
</li><li>You are motivated by the opportunity to apply cutting-edge technology to solve meaningful, real-world problems at a massive scale.
</li></ul>#LI-ES1
#LI-Hybrid</div>

Lead AI Engineer

NTT DATA

Req ID: 366565
 
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
 
We are currently seeking a Lead AI Engineer to join our team in Parsippany, New Jersey (US-NJ), United States (US).
 
We are seeking a Lead AI Engineer to drive developer productivity through Copilot‑first workflows, Generative AI solutioning, and autonomous agent programming. This role is critical to advancing our Developer Experience (DX) strategy by enabling modern, AI‑augmented development practices across engineering teams.
 You will serve as a hands‑on technical leader and evangelist for GitHub Copilot, Microsoft Copilot Studio, and other generative AI products such as Microsoft Power Platform, while researching, evaluating, and operationalizing emerging AI capabilities that measurably improve how software is built and delivered.
 Success is defined by adoption, efficiency gains, and scalable enablement, not experimentation alone. 5+ years of experience required on the following:
 
Key Responsibilities
 GitHub Copilot Developer Productivity Evangelism
 Drive adoption and advanced usage of GitHub Enterprise and GitHub Copilot, including Copilot Chat and autonomous agent‑based workflows.
 <ul>
<li>Identify high‑impact use cases across the SDLC (coding, testing, refactoring, documentation, CI/CD).</li>
<li>Establish best practices, patterns, and guardrails for AI‑assisted development.</li>
</ul>
Generative AI Autonomous Agent Programming
 <ul>
<li>Design and implement agentic AI solutions that automate and orchestrate developer workflows.</li>
</ul>
Build and evaluate autonomous and semi‑autonomous agents for tasks such as code generation, validation, remediation, and
 
workflow automation.
 <ul>
<li>Prototype and productionize emerging AI technologies with clear DX value.</li>
</ul>
Copilot Studio Power Platform Enablement
 <ul>
<li>Build and extend copilots using Microsoft Copilot Studio to support engineering and operational use cases.</li>
<li>Leverage Power Platform (Power Automate, Power Apps) to integrate AI capabilities into existing tools and workflows.</li>
<li>Enable low‑code / pro‑code collaboration through reusable components and templates.</li>
</ul>
Platform Strategy Gap Identification
 <ul>
<li>Assess existing developer tooling and AI capabilities to identify gaps, redundancies, and opportunities.</li>
<li>Define scalable architectures and reusable frameworks for AI development.</li>
<li>Partner with security, platform, and architecture teams to ensure compliant and responsible AI usage.</li>
</ul>
Technical Leadership
 <ul>
<li>Act as a subject matter expert for Copilot platforms and Generative AI development tools.</li>
<li>Mentor engineers and influence teams through guidance, demos, and hands‑on enablement.</li>
<li>Contribute to roadmap planning for AI‑driven DX initiatives.</li>
</ul>
Required Qualifications
 <ul>
<li>Strong software engineering background with hands‑on experience (Python, Java, C#, or similar).</li>
<li>Practical experience building Generative AI solutions in production environments.</li>
<li>Experience with GitHub Copilot and AI‑assisted development workflows.</li>
<li>Familiarity with LLMs, prompt engineering, embeddings, and RAG patterns.</li>
<li>Proven ability to evaluate and operationalize emerging technologies.</li>
</ul>
Preferred Qualifications
 <ul>
<li>Experience with autonomous or agentic AI programming.</li>
<li>Hands‑on experience with Microsoft Copilot Studio and Power Platform.</li>
<li>Background in Developer Experience (DX), platform engineering, or productivity tooling.</li>
<li>Experience working in large‑scale or regulated enterprise environments.</li>
</ul>
What Success Looks Like
 <ul>
<li>Measurable improvements in developer velocity and workflow efficiency.</li>
<li>Broad adoption of Copilot‑based development practices.</li>
<li>Reduced friction across the software development lifecycle.</li>
<li>Scalable, reusable AI patterns adopted across teams.</li>
</ul>
Why This Role Matters
 <ul>
<li>You will shape how AI transforms software development at scale.</li>
<li>You’ll influence modern, Copilot‑first engineering workflows.</li>
<li>Your work will directly enable engineers to focus on higher‑value problem solving.</li>
<li>You’ll help define the future of AI‑driven developer productivity.</li>
</ul>
This role researches, evaluates, and supports the adoption of emerging technologies, including identifying effective AI use cases to drive
 efficiency. It applies core software engineering principles to design, develop, test, integrate, and maintain applications that deliver business
 value. The role manages the full system development lifecycle, ensuring solutions are delivered on time, within budget, and successfully
 implemented. It provides deep functional and subject‑matter expertise, interpreting business challenges and recommending best practices to
 solve complex problems. While primarily an individual contributor, the role may act as a player‑coach, leading projects or teams and operating
 independently with guidance only in the most complex situations.
 
Agile Engineering Best Practices
 <ul>
<li>Identifies and recommends improvements to the software development lifecycle and best practices in agile engineering.</li>
<li>Provides input into various software development strategies (e.g., unit testing, acceptance testing, continuous delivery and integration,</li>
</ul>
release and deployment for frequent and reliable release), providing the case for using agile vs. traditional methodologies.
 <ul>
<li>Develops the roadmap and guidelines for tailoring agile practices to a complex and dynamic software development project.</li>
</ul>
Project Management
 <ul>
<li>Prioritizes multiple project plans, making final decisions about priorities, timing and resources.</li>
<li>Keeps abreast of the progress of multiple projects within a program or across the department; coaches project managers to adjust priorities or timelines as needed.</li>
<li>Monitors resource usage across projects or programs, identifying areas or synergy or redundancy and looking for ways to optimize efficiency.</li>
</ul>
Troubleshooting
 <ul>
<li>Provides guidance and expertise to analyze data and patterns and assess the root cause of complex, non-routine problems.</li>
<li>Collaborates with others across disciplines to brainstorm and execute solutions to the most complex, uncommon problems.</li>
<li>Guides the execution of solutions for complex, non-routine issues; redirects solution implementation if desired results were not originally met.</li>
</ul>
Application Development/Programming
 Identifies areas for improvement and develops innovative enhancements using available software development tools following design requirements of customer.
 
System and Technology Integration
 Interprets internal/external business challenges and recommends integration of the appropriate systems, applications and technology to
 provide a fully functional solution to a business problem.
 <ul>
<li>Exceeds customers’ expectations by listening for unexpressed needs; connects customer needs to relevant service offerings and new technology.</li>
<li>Leads others in resolving technical issues in a timely manner; follows up with customers to ensure satisfaction.</li>
<li>Partners with the business to integrate new technologies into business solutions; creates and communicates a vision of the technology requirements for the future state of the business</li>
</ul>
About NTT DATA
 
NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in RD.
 
Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact-us.
 
NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.

VeeRteq Solutions Inc.

<div>We are seeking a high-caliber AI Tech Lead / AI Engineer to design, build, and operationalize agentic AI solutions that accelerate analytics and reporting delivery. This role goes beyond basic agent creation and requires hands-on experience with agent orchestration, memory, and enterprise-grade data access patterns, delivering scalable components that fit into an existing framework while rapidly adapting to incoming business requests.
Responsibilities: -
<ul><li>Design, Architect, implement, and iterate on agentic AI solutions to shorten the cycle time for analytics, log analysis, and reporting requests.</li>
<li>Design agent orchestration patterns (multi-agent workflows), tool/function calling, and memory approaches appropriate for enterprise deployments.</li>
<li>Define secure and scalable data access patterns for agents (retrieval, context building, and grounding), integrating with existing data sources and governance expectations.</li>
<li>Partner closely with product, analytics, and engineering stakeholders to intake requirements quickly and deliver working prototypes and production-ready solutions.</li>
<li>Engineer reusable components and best practices that enable scalable delivery (not one-off scripts), aligned to an existing base framework.</li>
<li>Operationalize solutions for reliability and maintainability: testing strategies, monitoring/observability, prompt/version management, and deployment automation.</li>
<li>Evaluate build vs. buy options pragmatically when needed, while keeping focus on shipping solutions on the current platform stack.</li>
</ul>Tech Stack (Core): -
<ul><li>Cloud: AWS (primary deployment environment; open to alternatives)</li>
<li>Data/Analytics Platform: Databricks (including native &quot;chat with data&quot; capabilities and potential agent integrations)</li>
<li>Agent Frameworks: LangChain, LangGraph</li>
<li>Conversational analytics patterns: Ask-questions-on-data / conversational BI approaches (agent-driven analytics and dashboards</li>
</ul>Experience: -
10+ Years
Location: -
Rosemont, IL (3days/Week)
Educational Qualifications: -
Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
Technical certification in multiple technologies is desirable.
Skills: -
Mandatory skills
<ul><li>Demonstrated experience delivering agentic AI solutions beyond prototypes, including enterprise deployment considerations.</li>
<li>Strong hands-on engineering background with AWS-based deployments.</li>
<li>Experience working with modern data platforms (e.g., Databricks) and integrating LLM solutions with analytics/data ecosystems.</li>
<li>Ability to operate as a senior individual contributor who can define architecture and implement key pieces end-to-end.</li>
</ul>Excellent communication and collaboration skills with US-based stakeholders
Skills &amp; Expertise Needed
<ul><li>Agentic AI engineering: building and deploying LLM-powered agents for real business workflows.</li>
<li>Agent orchestration: designing multi-step and/or multi-agent flows; managing tool use, control flow, retries, and failure handling.</li>
<li>Agent memory: short-term and long-term memory patterns; conversation state; summarization and context window management.</li>
<li>Enterprise data access patterns for agents: retrieval/grounding strategies; context assembly from structured and unstructured sources; performance-conscious access.</li>
<li>Production deployment mindset: security, reliability, monitoring, and maintainability for enterprise-grade AI services.</li>
<li>Architecture &amp; best practices: ability to design scalable components that fit into an existing framework and can be extended by the team.</li>
<li>Rapid requirements intake: quickly translating ambiguous reporting/analytics asks into implementable solutions and iterating with stakeholders.</li>
<li>High autonomy: tech-lead level capability without direct people management; self-directed and able to set engineering direction for the workstream</li>
</ul>Good-to-Have Skills
<ul><li>Experience implementing retrieval-augmented generation (RAG) and hybrid retrieval across structured/unstructured sources.</li>
<li>Experience with LLMOps practices: prompt/version management, automated evaluation, and regression testing.</li>
<li>Experience building observability for AI systems (quality metrics, traces, latency/cost monitoring).</li>
<li>Familiarity with Databricks-specific agent or model serving patterns (where applicable).</li>
</ul>Experience building lightweight analytics experiences on top of agent outputs (e.g., auto-generated insights/dashboards).</div>

AI Tech Lead / AI Engineer

Shahzada Group of Industries

We are seeking an experienced AI Infrastructure &amp; Automation Engineer to join our team. In this role, you will be the bridge between high-level AI application logic and the underlying hardware that powers it. You will own the responsibility of scaling our AI operations, ensuring our LLM workflows run efficiently on centralized GPU infrastructure, and automating our backend systems. If you have a passion for building robust AI pipelines and optimizing server performance, we want to hear from you.Key Responsibilities<ul><li>Infrastructure Management: Architect, deploy, and maintain centralized GPU server clusters to ensure high availability and performance for LLM training and inference.</li><li>LLM Integration: Develop and maintain backend logic to integrate Large Language Models (LLMs) into production-grade applications.</li><li>Automation: Build end-to-end automation workflows that reduce manual operational tasks, utilizing tools like N8N, Make, or custom Python scripts.</li><li>System Optimization: Monitor and tune server resources to maximize GPU utilization and minimize inference latency.</li><li>Pipeline Development: Create and manage data pipelines for ingestion, preprocessing, and model fine-tuning.</li><li>Scalability: Troubleshoot hardware/software bottlenecks and scale our infrastructure as our AI service demand grows.</li></ul>Required Qualifications<ul><li>Deep Technical Expertise: 3+ years of experience in AI/ML infrastructure, systems engineering, or a similar technical role.</li><li>GPU &amp; Server Knowledge: Hands-on experience with managing GPU-accelerated servers (e.g., NVIDIA stack, CUDA, and containerization with Docker/Kubernetes).</li><li>LLM Proficiency: Practical experience with deploying and fine-tuning LLMs (e.g., Llama, OpenAI API, Mistral) in production environments.</li><li>Programming: Strong proficiency in Python and experience with MLOps frameworks.</li><li>System Integration: Proven ability to connect APIs, webhooks, and databases to build cohesive, automated business workflows.</li><li>Problem-Solving: A &quot;builder&quot; mindset with the ability to identify infrastructure bottlenecks and implement solutions proactively.</li></ul>Job Type: Full-timePay: Rs80,000.00 - Rs120,000.00 per monthWork Location: In person

Lead AI Automation Engineer (LLM & GPU Infrastructure)

Finaira

<div>
 The Principal AI Engineer provides technical leadership and direction for a team of AI Engineer, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives.
 
 
 
 Focus:
 
 End-to-End Initiative Leadership, AI/ML Strategy &amp; Mentorship
 
 
 
 The difference you will make:
 
 
 
 <ul>
 <li>
 Provide technical leadership, guidance, and mentorship to a team of AI Engineer
 </li>
 <li>
 Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production
 </li>
 <li>
 Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans
 </li>
 <li>
 Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing
 </li>
 <li>
 Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments
 </li>
 <li>
 Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation
 </li>
 <li>
 Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency
 </li>
 <li>
 Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth
 </li>
 <li>
 Act as a primary technical point of contact for stakeholders regarding AI solutions
 </li>
 <li>
 Hands-on contribution to critical code components, architectural design, and complex problem-solving
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 What you will bring to the role:
 
 
 
 
 Education:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred
 
 
 </li>
 </ul>
 
 Experience:
 
 
 
 <ul>
 <li>
 8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end
 
 
 </li>
 </ul>
 
 Technical Skills:
 
 
 
 <ul>
 <li>
 Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras)
 </li>
 <li>
 Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving
 </li>
 <li>
 In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes)
 </li>
 <li>
 Strong architectural skills for building robust, scalable, and maintainable AI infrastructures
 </li>
 <li>
 Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services
 </li>
 <li>
 Excellent understanding of data engineering principles, data governance, and database technologies
 </li>
 <li>
 Ability to evaluate and make sound technical decisions on complex trade-offs
 
 
 </li>
 </ul>
 
 Soft Skills:
 
 
 
 <ul>
 <li>
 Exceptional leadership, communication, and presentation skills, with the ability to influence and persuade stakeholders at all levels, including executive leadership
 </li>
 <li>
 Proven ability to think strategically and translate complex business challenges into innovative and impactful data science initiatives
 </li>
 <li>
 Strong mentoring and coaching skills, with a passion for developing the talents of junior team members
 </li>
 <li>
 Excellent collaboration and negotiation skills, with the ability to work effectively across diverse, cross-functional teams and build strong relationships
 
 
 </li>
 </ul>
 Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.
</div>

Principal AI Engineer

<div>The Principal AI Engineer provides technical leadership and direction for a team of AI Engineer, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives. 
Focus: End-to-End Initiative Leadership, AI/ML Strategy &amp; Mentorship
The difference you will make:<ul><li>
Provide technical leadership, guidance, and mentorship to a team of AI Engineer.</li><li>
Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production.</li><li>
Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans.</li><li>
Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing.</li><li>
Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments.</li><li>
Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation.</li><li>
Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency.</li><li>
Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth.</li><li>
Act as a primary technical point of contact for stakeholders regarding AI solutions.</li><li>
Hands-on contribution to critical code components, architectural design, and complex problem-solving.</li></ul> 

Requirements 
What you will bring to the role:
Education:<ul><li>
Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred.</li></ul>
Experience:<ul><li>
8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end.</li></ul>
Technical Skills:<ul><li>
Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras).</li><li>
Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving.</li></ul><ul><li>
In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes).</li><li>
Strong architectural skills for building robust, scalable, and maintainable AI infrastructures.</li><li>
Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services.</li><li>
Excellent understanding of data engineering principles, data governance, and database technologies.</li><li>
Ability to evaluate and make sound technical decisions on complex trade-offs.</li></ul>
Soft Skills:<ul><li>
Exceptional leadership, communication, and presentation skills, with the ability to influence and persuade stakeholders at all levels, including executive leadership.</li><li>
Proven ability to think strategically and translate complex business challenges into innovative and impactful data science initiatives.</li><li>
Strong mentoring and coaching skills, with a passion for developing the talents of junior team members.</li><li>
Excellent collaboration and negotiation skills, with the ability to work effectively across diverse, cross-functional teams and build strong relationships.</li></ul>
Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.</div>

Director of Artificial Intelligence

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Lead AI Engineer

Lead AI Engineer

AI Tech Lead / AI Engineer

Lead AI Automation Engineer (LLM & GPU Infrastructure)

Principal AI Engineer

Principal AI Engineer

Director of Artificial Intelligence