Engineer

Job Description Job Summary: We are looking for motivated and enthusiastic trainees with a strong foundation in programming and emerging technologies. The ideal candidates should have hands‑on knowledge of modern programming languages, familiarity with AI‑enabled tools, and strong communication skills to effectively collaborate with teams and stakeholders. Key Responsibilities Develop and Enhance GenAI Solutions: Build, fine‑tune, and optimize LLM‑based applications, ensuring high accuracy, reliability, and performance. Implement RAG and AI Pipelines: Create end‑to‑end GenAI workflows using vector databases, embeddings, and cloud‑based model orchestration. Integrate AI into Products: Work with APIs, microservices, and backend systems to embed GenAI features into applications at scale. Monitor and Improve Model Performance: Conduct evaluations, A/B tests, and model drift checks while applying prompt engineering and optimization techniques. Collaborate and Ensure Responsible AI: Partner with cross‑functional teams to implement secure, compliant, and ethically aligned AI systems. Qualification And Specialization Required Skills & Qualifications: Design, build, and optimize GenAI solutions using LLMs, transformer‑based models, and multimodal architectures for real-world business applications. Fine‑tune and evaluate pre‑trained models (e.g., GPT, Llama, Claude, Gemini) using domain‑specific datasets to improve accuracy and performance. Develop scalable AI pipelines including data ingestion, model training, inference services, and deployment on cloud platforms (Azure/AWS/GCP). Implement Retrieval‑Augmented Generation (RAG) using vector databases (Pinecone, FAISS, Chroma DB, Azure AI Search) to enable enterprise‑grade QA and summarization systems. Integrate GenAI models into applications via APIs, SDKs, microservices, or custom backend frameworks (Python/Node.js). Optimize model performance through prompt engineering, model compression, quantization, and latency reduction techniques. Collaborate with cross‑functional teams (data engineers, product owners, designers) to translate business needs into AI capabilities. Ensure security, compliance, and responsible AI practices including data privacy, model monitoring, bias mitigation, and ethical guidelines. Conduct experimentation and benchmarking to evaluate model performance, run A/B tests, and document results for continuous improvement. Stay up to date with the latest advancements in generative AI, LLM frameworks, and open‑source tools while contributing to internal innovation initiatives. TCS Employee Benefits Summary Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. Salary Range: $100,000–$120,000 a year Qualifications: BACHELOR OF COMPUTER SCIENCE #J-18808-Ljbffr