
Lead / Associate Architect - AIML - (Bangalore Location)
3 days ago
We are looking for AIML - Lead / Associate Architect / Architects to Join us as early as possible
Experience - 8+ years
Location - Bangalore (Hybrid)
Notice Period - 0 to 45 days
Interview Process - 3 to 4 level interviews (One level will be In Person interview at Aziro Chennai / Bangalore / Noida / Pune Office)
Job Description:
We are looking for a highly skilled Python Developer with hands-on experience in Generative AI platforms (such as Agentforce, N8, Microsoft Copilot Studio, or equivalent) and proficiency in GitHub workflows. The role involves building, integrating, and deploying intelligent applications that leverage modern AI frameworks and automation capabilities.
Key Responsibilities
- Design, develop, and optimize applications using Python.
- Build and integrate solutions using Generative AI platforms (Agentforce, N8, MS Copilot Studio, or similar).
- Develop AI-powered agents, copilots, and workflow automation tools for business use cases.
- Collaborate with cross-functional teams to translate business requirements into scalable technical solutions.
- Manage source code, versioning, and collaboration using GitHub (repos, actions, CI/CD).
- Conduct code reviews, testing, and debugging to ensure performance and reliability.
- Stay up to date with the latest advancements in AI/ML, automation, and software engineering practices.
Required Skills & Qualifications
- Strong programming expertise in Python (APIs, data structures, automation scripts, frameworks).
- Experience with Generative AI platforms (Agentforce, N8, Microsoft Copilot Studio, or other LLM-based platforms).
- Understanding of AI/ML concepts, prompt engineering, and conversational AI.
- Proficiency in GitHub for version control, collaboration, and CI/CD workflows.
- Experience with REST APIs, JSON, and cloud integrations (Azure, AWS, or GCP preferred).
- Problem-solving mindset with ability to work in agile environments.
Nice-to-Have Skills
Exposure to LangChain, LlamaIndex, or RAG-based architectures.
Knowledge of DevOps tools (Docker, Kubernetes, Terraform).
Familiarity with data processing libraries (Pandas, NumPy) and visualization tools.
Contributions to open-source projects on GitHub.
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