A
- Erfahrung
- 3+ Jahre
- Gehalt
- —
- Stellenangebote
- 1
- Veröffentlicht
- vor 6 Stunden
- Arbeitsmodus
- Im Büro
- Ausbildung
- None
- Teilnahmeberechtigung
- Candidates with no formal graduation requirement may apply.
- Wieder aufnehmen
- Bewerbung erforderlich
Wo Sie arbeiten werden
Stellenbeschreibung
Overview
Join Alterdomus India Private Limited as an AI & ML Engineer in Hyderabad, focusing on developing advanced AI solutions integrated into enterprise products.
Key Responsibilities
- Develop and maintain AI and machine learning pipelines, integrating large language model (LLM) APIs within Alter Domus product offerings.
- Create agentic AI workflows leveraging frameworks such as LangChain, LangGraph, AutoGen, and protocols like MCP/A2A.
- Integrate AI assistant capabilities with enterprise systems through RESTful APIs, webhooks, and microservice architectures.
- Utilize low-code development platforms and AI-assisted programming tools to quickly prototype innovative AI solutions.
- Implement and maintain unit and integration testing and manage continuous integration/continuous deployment (CI/CD) workflows using Docker and Kubernetes.
- Optimize prompt engineering techniques, refine prototypes iteratively, and facilitate knowledge base vectorization processes.
Required Qualifications & Experience
- Minimum 3 years of practical experience with Python programming and related libraries including NumPy, Pandas, PyTorch, and TensorFlow.
- Hands-on expertise in building agentic AI workflows using LangChain, LangGraph, AutoGen, or CrewAI.
- Proficiency with vector databases such as Pinecone or Qdrant and comprehensive understanding of natural language processing (NLP) and retrieval-augmented generation (RAG).
- Demonstrated experience developing and integrating REST APIs and working within microservice architectures.
- Familiarity with cloud platforms like AWS, Azure, or Google Cloud Platform alongside containerization technologies including Docker and Kubernetes.
- Strong skills in prompt engineering and tuning large language models through platforms such as Azure OpenAI or AWS Bedrock APIs.
Fähigkeiten
Maschinelles Lernen
Prompt Engineering
Python Programming
RESTful API Development
Cloud platforms (AWS, Azure, GCP)
Containerization (Docker, Kubernetes)
Deep learning frameworks (PyTorch, TensorFlow)
microservice architecture
LangChain and agentic AI frameworks
Vector databases (Pinecone, Qdrant)
Large Language Models tuning