People Impact

As Senior Manager – AI Engineering, you will be responsible for driving the strategic direction, capability maturity, and delivery outcomes of GenAI solutions . This includes managing cross-functional pods, enabling reusable frameworks for agentic workflows, and translating AI/LLM advancements into business-impacting applications. You will lead a high-performing team of AI engineers and collaborate across product, engineering, and platform teams to scale our AI first approach.

Sr. Software Engineer

Role expects you to

• Design, code, test, debug, deploy Web App and Mobile Apps

• Collaborate with SMEs to resolve Technical Issues and Achieve Goals

• Lead Projects, teams

• Strong problem solving skills

• Open to learn new technologies

Qualification

▪ 4+ years of IT Development Experience

▪ Comprehensive Programming Experience in Web and Mobile app development using

MEAN or MERN stack

▪ Knowledge of Python, Ruby

▪ Knowledge of RDBMS like MS SQL, PostgreSQL, MySQL

▪ Understanding of Dev-Ops Tools like git, Jenkins, Azure Dev-Ops

▪ Exposure Cloud technologies, Agile development process, Estimation techniques

▪ Understanding of End to End Development process

Technical Expertise

• Advanced proficiency in Python
• Expertise in Deep Learning Frameworks: PyTorch and TensorFlow
• Experience with Computer Vision Models:
• YOLO (Object Detection)
• UNet, Mask R-CNN (Segmentation)
• Deep SORT (Object Tracking)

Real-Time & Deployment Skills

• Real-time video analytics and inference optimization
• Model pipeline development using:
• Docker
• Git
• MLflow or similar tools
• Image processing proficiency: OpenCV, NumPy
• Deployment experience on Linux-based GPU systems and edge devices (Jetson Nano, Google Coral, etc.)

Professional Background

• Minimum 4+ years of experience in AI/ML, with a strong focus on Computer Vision and System-Level Design
• Educational qualification: B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or a related field
• Strong project portfolio or experience in production-level deployments

1. Curriculum Development: Collaborate with Academic Advisory Committee and Marketing team members to design and develop comprehensive curriculum for data science programs at undergraduate and graduate levels. Ensure alignment with industry trends, emerging technologies, and best practices in data science education.
2. Faculty Recruitment and Development: Lead the recruitment, selection, and development of faculty members with expertise in data science. Provide mentorship, support, and professional development opportunities to faculty to enhance teaching effectiveness and academic performance.
3. Quality Assurance: Establish and maintain robust mechanisms for quality assurance and academic oversight. Implement assessment strategies, evaluation criteria, and continuous improvement processes to ensure the delivery of high-quality education and student outcomes.
4. Student Engagement: Foster a culture of student engagement, innovation, and success. Develop initiatives to support student learning, retention, and career readiness in the field of data science. Provide academic counselling and support services to students as needed.
5. Industry Collaboration: Collaborate with industry partners, employers, and professional organizations to enhance experiential learning opportunities, internships, and job placement prospects for students. Organize industry events, guest lectures, and networking opportunities to facilitate knowledge exchange and industry engagement.
6. Research and Innovation: Encourage research and innovation in data science education. Facilitate faculty research projects, interdisciplinary collaborations, and scholarly activities to advance knowledge and contribute to the academic community.

Budget Management: Develop and manage the academic budget in collaboration with the finance department. Ensure efficient allocation of resources to support academic programs, faculty development, and student services.

·                    Design, develop, and implement AI/ML models and algorithms.

·                    Focus on building Proof of Concept (POC) applications to demonstrate the feasibility and value of AI solutions.

·                    Write clean, efficient, and well-documented code.

·                    Collaborate with data engineers to ensure data quality and availability for model training and evaluation.

·                    Work closely with senior team members to understand project requirements and contribute to technical solutions.

·                    Troubleshoot and debug AI/ML models and applications.

·                    Stay up-to-date with the latest advancements in AI/ML.

·                    Utilize machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) to develop and deploy models.

·                    Develop and deploy AI solutions on Google Cloud Platform (GCP).

·                    Implement data preprocessing and feature engineering techniques using libraries like Pandas and NumPy.

·                    Utilize Vertex AI for model training, deployment, and management.

·                    Integrate and leverage Google Gemini for specific AI functionalities.

Qualifications:

·                    Bachelor’s degree in computer science, Artificial Intelligence, or a related field.

·                    3+ years of experience in developing and implementing AI/ML models.

·                    Strong programming skills in Python.

·                    Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.

·                    Good understanding of machine learning concepts and techniques.

·                    Ability to work independently and as part of a team.

·                    Strong problem-solving skills.

·                    Good communication skills.

·                    Experience with Google Cloud Platform (GCP) is preferred.

·                    Familiarity with Vertex AI is a plus.

Role Overview

We are seeking a highly skilled and experienced Senior AI Engineer with deep expertise in computer vision and architectural design. The ideal candidate will lead the development of robust, scalable AI systems, drive architectural decisions, and contribute significantly to the deployment of real-time video analytics, multi-model systems, and intelligent automation

solutions.

Key Responsibilities

 Design and lead the architecture of complex AI systems in the domain of computer vision and real-time inference.

 Build and deploy models for object detection, image segmentation, classification, and tracking.

 Mentor and guide junior engineers on deep learning best practices and scalable software engineering.

 Drive end-to-end ML pipelines: from data ingestion and augmentation to training, deployment, and monitoring.

 Work with YOLO-based and transformer-based models for industrial use-cases.

 Lead integration of AI systems into production with hardware, backend, and DevOps teams.

 Develop automated benchmarking, annotation, and evaluation tools.

 Ensure maintainability, scalability, and reproducibility of models through version control, CI/CD, and containerization.

Required Skills

 Advanced proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).

 Strong experience with YOLO, segmentation networks (UNet, Mask R-CNN), and

tracking (Deep SORT).

 Sound understanding of real-time video analytics and inference optimization.

 Hands-on experience designing model pipelines using Docker, Git, MLflow, or similar tools.

 Familiarity with OpenCV, NumPy, and image processing techniques.

 Proficiency in deploying models on Linux systems with GPU or edge devices (Jetson, Coral)

Good to Have

 Experience with multi-model orchestration, streaming inference (DeepStream), or virtual camera inputs.

 Exposure to production-level MLOps practices.

 Knowledge of cloud-based deployment on AWS, GCP, or DigitalOcean.

 Familiarity with synthetic data generation, augmentation libraries, and 3D modeling tools.

 Publications, patents, or open-source contributions in the AI/ML space.

Qualifications

 B.E./B.Tech/M.Tech in Computer Science, Electrical Engineering, or related field.

 4+ years of proven experience in AI/ML with a focus on computer vision and system- level design.

 Strong portfolio or demonstrable projects in production environments

Instructional Designer – eLearning Development

📍 Location: Chennai / Hyderabad (Hybrid)

🕐 Shift: 11 AM – 7 PM / 3 PM – 12 AM

🗣️ Communication: Excellent (Mandatory)

📅 Experience: 8–12 years in Instructional Design

About the Role:

We’re hiring an experienced Instructional Designer to craft impactful and interactive corporate learning experiences. If you're hands-on with tools like Storyline, Vyond, Adobe XD, and have a passion for innovation in learning, we want to hear from you.

Key Responsibilities:

• Design and develop eLearning content using Storyline, Rise, Camtasia, Captivate, and Lectora
• Provide clear development instructions to course developers
• Create custom interactives, interactive videos, and conceptual maps
• Hands-on video creation using Vyond, Powtoon, Synthesia
• Develop 2D/3D digital character illustrations
• Apply design thinking, UI/UX principles, and interaction design
• Collaborate with global stakeholders, especially US-based teams

Must-Have Skills:

• Authoring Tools: Storyline, Rise, Captivate, Camtasia, Lectora
• Video Tools: Vyond, Powtoon, Adobe Creative Suite, Synthesia
• Design Skills: Adobe XD, Custom Interactives, Concept Mapping
• Illustration: 2D/3D Digital Characters
• Corporate Content Experience (Healthcare is a plus)

Job Title: AI Solutioning Architect – Healthcare IT

Role Summary:

The AI Solutioning Architect leads the design and implementation of AI-driven solutions across the organization, ensuring alignment with business goals and healthcare IT standards. This role defines the AI/ML architecture, guides technical execution, and fosters innovation using platforms like Google Cloud (GCP).

Key Responsibilities:

• Architect scalable AI solutions from data ingestion to deployment.
• Align AI initiatives with business objectives and regulatory requirements (HIPAA).
• Collaborate with cross-functional teams to deliver AI projects.
• Lead POCs, evaluate AI tools/platforms, and promote GCP adoption.
• Mentor technical teams and ensure best practices in MLOps.
• Communicate complex concepts to diverse stakeholders.

Qualifications:

• Bachelor’s/Master’s in Computer Science or related field.
• 12+ years in software development/architecture with strong AI/ML focus.
• Experience in healthcare IT and compliance (HIPAA).
• Proficient in Python/Java and ML frameworks (TensorFlow, PyTorch).
• Hands-on with GCP (preferred) or other cloud platforms.
• Strong leadership, problem-solving, and communication skills.

Job Title: Data Warehouse/Redshift Admin

Location: Remote

Job Description

AWS Redshift Cluster Planning

AWS Redshift Cluster Maintenance

AWS Redshift Cluster Security

AWS Redshift Cluster monitoring.

Experience managing day to day operations of provisioning, maintaining backups, DR and monitoring of AWS RedShift/RDS clusters

Hands-on experience with Query Tuning in high concurrency environment

Expertise setting up and managing AWS Redshift

AWS certifications Preferred (AWS Certified SysOps Administrator)