AI / ML Engineer

AI ML Engineer (GenAI) - Assistant Manager

Position Summary

GenAI Engineer – CL4

Role Overview: As a GenAI Engineer, you will
actively engage in your engineering craft, taking a hands-on approach to
multiple high-visibility projects. Your expertise will be pivotal in delivering
solutions that delight customers and users,  You will leverage your extensive GenAI &
engineering craftmanship across multiple programming languages and modern
frameworks, consistently demonstrating your strong track record in delivering
high-quality, outcome-focused solutions. The ideal candidate will be a
dependable team player, collaborating with cross-functional teams to design,
develop, and deploy advanced software solutions.

Key Responsibilities:

Outcome-Driven
Accountability: Embrace
and drive a culture of accountability for customer and business outcomes.
Develop engineering solutions that solve complex problems with valuable
outcomes, ensuring high-quality, lean designs and implementations.

Technical
Leadership and Advocacy: Serve as the technical advocate for products, ensuring
code integrity, feasibility, and alignment with business and customer goals.
Lead requirement analysis, component design, development, unit testing,
integrations, and support.

Engineering
Craftsmanship: Maintain
accountability for the integrity of code design, implementation, quality, data,
and ongoing maintenance and operations. Stay hands-on, self-driven, and
continuously learn new approaches, languages, and frameworks with significant
focus on infusing AI/ML/GenAI where possible/appropriate. Create technical
specifications, and write high-quality, supportable, scalable code ensuring all
quality KPIs are met or exceeded. Demonstrate collaborative skills to work
effectively with diverse teams.

Customer-Centric
Engineering: Develop
lean engineering solutions through rapid, inexpensive experimentation to solve
customer needs. Engage with customers and product teams before, during, and
after delivery to ensure the right solution is delivered at the right time.

Incremental
and Iterative Delivery: Adopt a mindset that favors action and evidence
over extensive planning. Utilize a learning-forward approach to navigate
complexity and uncertainty, delivering lean, supportable, and maintainable
solutions.

Cross-Functional
Collaboration and Integration: Work collaboratively with empowered,
cross-functional teams including product management, experience, and delivery.
Integrate diverse perspectives to make well-informed decisions that balance
feasibility, viability, usability, and value. Foster a collaborative environment
that enhances team synergy and innovation.

Advanced
Technical Proficiency: Possess deep expertise in modern software
engineering practices and principles, including AI/ML/GenAI, Agile
methodologies and DevSecOps to deliver daily product deployments using full
automation from code check-in to production with all quality checks through
SDLC lifecycle. Strive to be a role model, leveraging these techniques to
optimize solutioning and product delivery. Demonstrate understanding of the
full lifecycle product development, focusing on continuous improvement and
learning.

Domain
Expertise: Quickly
acquire domain-specific knowledge relevant to the business or product.
Translate business/user needs, architectures, and UX/UI designs into technical
specifications and code. Be a valuable, flexible, and dedicated team member,
supportive of teammates, and focused on quality and tech debt payoff.

Effective
Communication and Influence: Exhibit exceptional communication skills, capable
of articulating complex technical concepts clearly and compellingly. Inspire
and influence teammates and product teams through well-structured arguments and
trade-offs supported by evidence. Create coherent narratives that align
technical solutions with business objectives.

Engagement
and Collaborative Co-Creation: Engage and collaborate with product engineering
teams at all organizational levels, including customers as needed. Build and
maintain constructive relationships, fostering a culture of co-creation and
shared momentum towards achieving product goals. Align diverse perspectives and
drive consensus to create feasible solutions.

Requirements

Key Qualifications:

§  A bachelor’s degree in computer science,
software engineering, or a related discipline. An advanced degree (e.g., MS) is
preferred but not required. Experience is the most relevant factor.

§  Strong software engineering foundation
with deep understanding of OOPs, data-structure, algorithms, code
instrumentations, beautiful coding practices etc.

§  5+ years of experience with AI/ML, with
last 2 years focused on GenAI as well as technologies like OpenAI, Claude,
Gemini, LangChain, Agents, Vector databases, and approaches like Prompt
Engineering, fine-tuning, etc.

§  Proven experience in: Python, R,
TensorFlow, PyTorch, Keras, Julia, ML libraries, NLP, etc.

§  Proven experience with big data
technologies, Angular, React, NodeJS, Python, C#, .NET Core, Java, Golang,
SQL/NoSQL.

§  Proven experience with cloud-native
engineering, using FaaS/PaaS/micro-services on cloud hyper-scalers like Azure,
AWS, and GCP.

§  Strong understanding of methodologies
& tools like, XP, Lean, SAFe, DevSecOps, SRE, ADO, GitHub, SonarQube, etc.

§  Excellent interpersonal and
organizational skills, with the ability to handle diverse situations, complex
projects, and changing priorities, behaving with passion, empathy, and care.