An AI Engineer designs, develops, and deploys AI models and solutions, including Generative AI applications, to solve real-world business problems. This role involves hands-on coding, model training, and integration into production systems.
Key Responsibilities :
– Design, build, and fine-tune machine learning, deep learning, and Generative AI models for real-world use cases.
– Develop Agentic AI systems using frameworks such as ADK, LangGraph, or equivalent for orchestration and reasoning.
– Build solutions leveraging LLMs, RAG pipelines, embeddings, and vector databases.
– Design and implement AI systems for text, structured/unstructured data, and conversational use cases.
– Apply core NLP techniques including classification, summarization, entity recognition, and semantic search.
– Develop scalable algorithms for search, retrieval, and real-time inference.
– Build and integrate AI microservices into enterprise systems using APIs, event-driven architectures, and cloud services.
– Deploy and operate AI workloads using Docker, Kubernetes, and managed cloud AI platforms (Azure ML, AWS SageMaker, GCP Vertex AI).
– Optimize solutions for performance, cost, latency, and security.
– Collect, preprocess, and manage large datasets for fine-tuning and inference.
– Continuously monitor and optimize models and prompts for accuracy, scalability, and efficiency.
– Partner with Solution Architects and business teams to translate requirements into production-ready AI solutions.
– Champion Responsible AI practices, including fairness, bias mitigation, and compliance.
Required Skills :
– Proficiency in Python, SQL, and ML frameworks (TensorFlow, PyTorch).
– Strong understanding of Generative AI concepts (transformers, embeddings, fine-tuning).
– Experience with Agentic AI frameworks (ADK, LangGraph, AutoGen).
– Familiarity with cloud platforms (AWS, Azure, GCP) for AI deployment.
– Knowledge of prompt engineering, vector databases (Pinecone, Weaviate), and retrieval-augmented generation (RAG).
– Hands-on with cloud-native AI deployments (Azure, AWS, GCP).
– Familiarity with API-driven design, microservices, and event-driven architectures.
Qualifications :
– Bachelor’s/Master’s in Computer Science, AI, Data Science, or related field.
– 3- 9 years of experience in AI/ML development and deployment.
– Hands-on experience with LLMs and Generative AI applications.
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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