Lead complex AI/ML initiatives, design, develop, evaluate, and operationalize enterprise AI solutions, mentor junior data scientists, and collaborate across engineering and product teams.
Compensation
The range listed is just one component of BMC's employee compensation package. The annual base salary range represents the low and high end of the BMC salary range for this position. Actual salaries depend on a wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training, licensure, and certifications; other business and organizational needs. The range listed is zł 251,025 - zł 418,375
Responsibilities
Design and develop AI/ML solutions
Evaluate and operationalize models
Mentor junior data scientists
Collaborate with AI Engineering and Platform Engineering
Lead technical decisions
Requirements
Bachelor’s degree in Machine Learning, Statistics, Data Science, Physics, Computer Science, or a related field
Design, develop, and deploy production‑grade Multi‑Agent Systems (MAS) and agentic workflows using Gemini Enterprise, integrating cloud or on‑prem pipelines and generative AI models.
Responsibilities
Design, develop, and deploy production‑grade Multi‑Agent Systems (MAS) and agentic workflows using Gemini Enterprise
Identify need for Pro Code Vs No Code design based on customer problem statement and data sources
Design Deploy and custom agents using the Agent Development Kit (ADK), and Agent Platform AI Reasoning Engine and integrate with Gemini Enterprise
Build native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail, Calendar, Meet) and NotebookLM for grounded enterprise research, document automation, and conversational discovery
Architect scalable short‑term session storage, conversation state persistence, and long‑term memory architectures across multi‑agent interactions
Design, develop, and deploy production‑grade multi‑agent systems and AI solutions using Google Gemini and related tools.
Responsibilities
Design, develop, and deploy production‑grade Multi‑Agent Systems (MAS) and agentic workflows using Gemini Enterprise
Identify need for Pro Code Vs No Code design based on customer problem statement and data sources
Design Deploy and custom agents using the Agent Development Kit (ADK), and Agent Platform AI Reasoning Engine and integrate with Gemini Enterprise
Build native integrations across the Google Workspace Ecosystem (Docs, Drive, Gmail, Calendar, Meet) and NotebookLM for grounded enterprise research, document automation, and conversational discovery
Architect scalable short‑term session storage, conversation state persistence, and long‑term memory architectures across multi‑agent interactions
AI Engineer at Thoughtworks applying deep knowledge of AI engineering, foundation models, context engineering, retrieval architectures, agentic systems and LLMOps to design, build and operationalize enterprise AI solutions.
Locations (4)
Bangalore, India
Chennai, Tamil Nadu, India
Hyderabad, Telangana, India
Pune, Maharashtra, India
Responsibilities
Collaborate with stakeholders to understand strategic objectives and identify opportunities to leverage data and data quality for enabling AI and machine learning
Responsible for overall AI system design, problem framing and governance, identifying and managing risks and issues
The salary range for this job is:
New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $166,900 to $278,100
Bay Area California offices – $173,800 to $289,700
All other offices locations in the US, including Sacramento – $139,100 to $254,900
Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.
Responsibilities
Partner with client stakeholders to understand business objectives, challenges, and opportunities.
Lead discovery, requirements definition, solution design, and implementation activities.
Design and deliver solutions across AI, cloud, data, digital, and platform engineering domains.
Translate business requirements into scalable architectures, delivery plans, and engineering workstreams.
Own solution delivery end-to-end, from problem definition through deployment and adoption.
Requirements
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Nice to have: Experience delivering AI solutions in financial services or another regulated industry
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