Company Description :

EncureIT Systems Private Limited, founded in September 2012, specializes in delivering professional information security services to clients across diverse industries.

The company focuses on niche areas such as application vulnerability scanning, penetration testing, secure architecture design, and mobile application security.

EncureIT also extends its expertise to product development, testing services, automation, AI technology and performance testing.

With a team of skilled professionals and a commitment to ensuring robust security, EncureIT offers tailored solutions to meet the needs of its customers.

Role Overview :

We are seeking a Senior Gen AI Engineer to lead the design, development, and deployment of advanced AI solutions across Generative AI, Deep Learning, and traditional ML.

This role requires not only strong technical expertise but also leadership in mentoring junior engineers, coordinating with cross-functional teams, and directly engaging with clients to understand problems and deliver impactful solutions.

You will take ownership of end-to-end AI/ML initiatives from business problem definition and data strategy to production deployment and ongoing optimization while ensuring scalability, robustness, and innovation in AI-driven products.

Key Responsibilities :

Leadership & Client Communication :

- Act as the technical lead for AI/ML projects, ensuring timely and high-quality delivery.

- Communicate directly with clients to gather requirements, present solutions, and provide technical insights.

- Lead technical discussions, demos, and presentations with clients and stakeholders.

- Coordinate and mentor junior AI/ML engineers, providing guidance on project tasks and technical challenges.

End-to-End AI/ML Lifecycle :

- Drive problem scoping, data collection, model development, deployment, monitoring, and continuous iteration.

- Translate complex business requirements into scalable ML/AI solutions.

Model Development (Generative + Traditional) :

- Build, fine-tune, and optimize transformer-based LLMs (GPT, BERT, LLaMA), GANs, diffusion models, and multimodal AI systems.

- Develop and improve ML/DL models for computer vision (CNNs, R-CNN, YOLO, etc.), NLP, and recommendation systems.

Data Engineering & Pipelines :

- Architect robust data pipelines (ETL/ELT), data labelling, pre-processing, and augmentation frameworks.

- Ensure versioning, reproducibility, and data governance practices.

MLOps & Deployment :

- Lead model containerization (Docker), microservice/API deployment, and CI/CD pipeline setup for ML.

- Implement monitoring, drift detection, scaling, and performance tracking for deployed models.

Troubleshooting & Optimization :

- Solve advanced AI challenges : hallucinations, overfitting, bias, imbalance, latency, and model interpretability.

- Optimize models for accuracy, efficiency, and cost.

Innovation & Research :

- Stay at the forefront of Gen AI, RAG frameworks, Lang Chain, and emerging ML research.

- Prototype and evaluate new architectures, libraries, and deployment approaches.

Collaboration & Documentation :

- Partner with product managers, DevOps, backend engineers, and clients to deliver integrated AI solutions.

- Document experiments, frameworks, and deployment architectures for team adoption and client transparency.

Required Skills :

- Bachelor's/Master's in Computer Science, AI, Data Science, or related field.

- 2-5 years of proven experience in ML/AI roles, with at least 2 years in leading/mentoring roles.

- Proficient in Python, ML/DL frameworks (PyTorch, TensorFlow, Hugging Face, scikit-learn).

- Expertise in LLM fine-tuning, generative models, and traditional ML.

- Strong grasp of AI/ML project lifecycle, MLOps, and cloud deployment (AWS/GCP/Azure).

- Skilled in data workflows, feature engineering, dataset versioning, and reproducibility.

- Hands-on experience with Docker, REST APIs, Git, and CI/CD pipelines.

- Excellent problem-solving, analytical, and debugging abilities.

- Strong communication skills with ability to manage client expectations.

Preferred Skills :

- Hands-on projects with ChatGPT, LLaMA, Stable Diffusion, multimodal AI, or vector DBs (FAISS, Pinecone, Weaviate).

- Experience in RAG pipelines, prompt engineering, and production-level Gen AI applications.

- Proven track record of leading teams, mentoring juniors, or client delivery.

- Contributions to open-source AI/ML projects, publications, or GitHub portfolio.

- Awareness of AI ethics, fairness, compliance, and data privacy regulations.