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Engineering Manager – Fullstack & AI Engineering

Codvo.ai
Remote

Apply Now

Job details

Full-time

Qualifications

CI/CD
Azure
Management
Node.js
Law
React
Software deployment
Master's degree
Microservices
AWS
Distributed systems
Continuous integration
Angular
APIs
AI
Leadership
Python

Full job description

Job Description: Engineering Manager – AI Engineering

Location: [Remote – India]

Experience: 8–14+ years

Role Type: Full-time

About Codvo.ai

Codvo.ai is a next-gen technology consulting and product engineering company

focused on delivering AI-driven digital transformation. We blend engineering

excellence, innovation, and a strong problem-solving culture to craft solutions that

scale. We partner with global enterprises across FinTech, Digital Commerce,

HealthTech, and Emerging Tech ecosystems.

If you are passionate about building teams, solving deep technical challenges, and

applying AI to accelerate product development — this role is for you.

About the Role

We are looking for an Engineering Manager – AI Engineering who combines people

leadership, technical depth, and hands-on programming expertise. You will lead a

high-performing engineering team that builds intelligent, scalable, and production

grade systems leveraging AI, automation, cloud, and modern full-stack frameworks.

This is a hybrid role that blends AI engineering, hands-on development, delivery

management, and team leadership.

Key Responsibilities

AI Engineering Leadership

Lead teams building AI-powered applications, intelligent automation, and data

driven solutions.

Guide engineers on integrating LLMs, vector search, prompt engineering, and AI

pipelines into products.

Partner with AI/ML specialists to convert POCs into scalable production

systems.

Hands-On Technical Contribution

(Must be 30–40% hands-on)

Contribute actively to codebases using Node.js, Python, React.js, Angular, and

related frameworks.

Design microservices, APIs, and cloud-native applications with AI components

embedded.

Perform code reviews, provide architectural direction, and ensure high

engineering standards.

Build reusable components, utilities, and internal tooling that accelerate AI

delivery.

Delivery & Execution

Own delivery excellence across sprints — scope planning, engineering

estimations, prioritization, dependency management, and stakeholder

alignment.

Drive high-quality, on-time delivery for AI and application engineering initiatives.
Ensure strong CI/CD, DevOps automation, and observability practices within the

team.

People Leadership

Lead, mentor, and coach a team of 6–12 engineers, AI developers, and tech

leads.

Conduct 1:1s, performance reviews, skill assessments, and career coaching.
Hire strong engineering talent and ensure smooth onboarding and competency

growth.

Build a culture of ownership, innovation, continuous learning, and

experimentation.

Architecture & Technical Direction

Work closely with architects to define scalable AI + application architectures.
Lead design discussions around distributed systems, API contracts, data flows,

and model integration.

Evaluate new AI tools, frameworks, and cloud services; make recommendations

for adoption.

Cross-Functional Collaboration

Partner with Product Managers, UX designers, AI/ML engineers, and DevOps

teams to deliver cohesive solutions.

Translate business problems into technical solutions with clear trade-offs and

measurable impact.

Communicate progress, risks, and technical decisions clearly to stakeholders

and customers.

Qualifications

Must Have

8–14+ years of engineering experience with 2–5+ years in team/people

management.

Strong hands-on programming expertise in:

o Node.js

o Python

o React.js

o Angular

Experience delivering AI-enabled applications, generative AI features, or ML

integrated systems.

Solid understanding of microservices, distributed systems, API design, and

cloud platforms (AWS/Azure/GCP).

Proven ability to lead engineering teams and deliver complex projects end-to

end.

Good to Have

Experience with vector DBs (Pinecone, Qdrant, Weaviate, PGVector).
Knowledge of LLM orchestration (LangChain, LlamaIndex, custom pipelines).
Exposure to MLOps, model deployment, and AI observability.
Experience with enterprise consulting/client-facing delivery.

Apply Now

Refine Your Search

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