Auxo AI

We are seeking a SAP Functional Consultant with experience in SAP S/4HANA and core manufacturing and supply chain processes, including Materials Management (MM), Production Planning (PP), Quality Management (QM), and Plant Maintenance (PM).

The ideal candidate will possess strong functional knowledge of SAP processes, hands-on configuration experience, and the ability to work closely with business and technology teams to support SAP implementation, enhancement, and transformation initiatives.

Key Responsibilities

• Support SAP functional design, configuration, testing, and deployment activities across MM, PP, QM, and PM modules.

• Gather and analyze business requirements and assist in translating them into SAP solutions.

• Configure and support business processes including:

o Materials Management and Procurement

o Production Planning and Manufacturing Operations

o Quality Management

o Plant Maintenance

o Inventory Management

o Master Data Management

• Participate in SAP S/4HANA implementation, enhancement, migration, and support projects.

• Assist in fit-gap analysis, process mapping, and solution design activities.

• Collaborate with technical teams on integrations, reports, interfaces, conversions, and enhancements.

• Support testing activities including SIT, UAT, defect resolution, and deployment validation.

• Prepare functional specifications, process documentation, training materials, and user guides.

• Support go-live activities, hypercare, and post-production support.

• Work closely with business users to troubleshoot issues and identify process improvement opportunities.

Required Skills & Experience

• 3–6 years of SAP functional consulting experience.

• Hands-on experience in one or more of the following SAP modules:

o SAP Materials Management (MM)

o SAP Production Planning (PP)

o SAP Quality Management (QM)

o SAP Plant Maintenance (PM)

• Experience working with SAP S/4HANA environments.

• Understanding of manufacturing, supply chain, procurement, inventory, and maintenance business processes.

• Experience supporting requirements gathering, configuration, testing, and deployment activities.

• Strong analytical, problem-solving, and communication skills.

• Ability to work effectively in a collaborative, team-oriented environment.

Preferred Qualifications

• Exposure to SAP Integrated Business Planning (IBP).

• Exposure to SAP Ariba and procurement processes.

• Experience supporting SAP ECC to S/4HANA migration initiatives.

• SAP certification in MM, PP, QM, PM, or S/4HANA.

• Experience working in manufacturing, life sciences, medical devices, consumer products, or supply chain-intensive industries.

What You'll Bring

• Strong functional and analytical capabilities.

• Ability to understand business requirements and translate them into SAP solutions.

• A proactive learning mindset and willingness to expand expertise across SAP modules.

• Strong collaboration and stakeholder engagement skills.

• Passion for driving operational excellence through SAP-enabled business processes.

AuxoAI is seeking a skilled and experienced Senior AI Engineers to join our dynamic team. The ideal candidate will have 5+ years of prior experience in software engineering. This role involves collaborating with cross-functional teams to drive innovation and deliver impactful AI-driven products. This role is responsible for implementing our strategic direction on AI, intelligent automation, and data-powered operations. This role will also guide the implementation of AI solutions across various projects, with an eye on AI governance.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

· AI/ML Solution Development: Design, develop, and deploy AI/ML technology stacks from concept to production and deployment

· Technical Leadership: Provide technical leadership and mentorship to junior engineers, guiding them in best practices and advanced techniques.

· Develop and optimize Generative AI workflows, including prompt engineering, fine-tuning, RAG and LLM-based applications.

· Work with Large Language Models (LLMs) such as Claude, Llama, Mistral, and GPT, ensuring efficient adaptation for various use cases.

· Design and implement AI-driven automation using agentic AI systems and orchestration frameworks like Autogen, LangGraph, and CrewAI.

· Leverage cloud AI infrastructure (AWS, Azure, GCP) for scalable deployment and performance tuning.

· Collaborate with cross-functional teams to deliver AI-driven solutions.

· Front ending customer discussions, customer engagement and success stories

· Collaborate with stakeholders to gather requirements and translate them into technical specifications

Requirements

Bachelor’s in computer science, Engineering, or a related field

· Overall 5+ year’s experience in software engineering and 2+ years of experience in AI/ML, with expertise in Generative AI and LLMs. 

· Experience with AWS Bedrock or Azure OpenAI studio or similar enterprise AI environments

· Strong proficiency in Python and experience with AI/ML frameworks like PyTorch and TensorFlow

· Experience with containerization (e.g., Docker, Kubernetes), version control systems (e.g., Git) and software development methodologies (e.g., Agile, Scrum)

· Knowledge of advanced prompt engineering techniques

· Experience in AI workflow automation and model orchestration

· Hands-on experience with API development using Flask or Django

Note: Given the urgency of the role, we are currently prioritizing candidates who can join immediately or within 2-3 weeks.

AuxoAI is seeking a Senior Applied Scientist to design and deploy structured knowledge systems that enable reliable, schema-grounded AI and agent reasoning.

This role sits at the intersection of large language models, knowledge graphs, semantic architectures, and hybrid retrieval systems. The ideal candidate will build systems that transform unstructured data into structured knowledge representations, enforce semantic constraints, and enable hybrid symbolic–neural reasoning in production environments.

You will play a key role in designing scalable semantic infrastructures that support advanced AI use cases such as GraphRAG pipelines, structured extraction, and agent reasoning workflows.

You will work on problems where existing architectures may not be sufficient and will experiment with new approaches that combine machine learning, knowledge graphs, semantic constraints, and classical AI techniques to build reliable, production-grade systems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

• Design schema-guided information extraction systems using zero-shot and few-shot structured prompting, constrained decoding approaches such as JSON schema enforcement or grammar-based decoding, and function-calling or tool-driven extraction techniques.
• Develop recursive or multi-stage extraction pipelines capable of handling nested entities, hierarchical structures, and cross-document relationships.
• Build ontology-driven systems using frameworks such as LinkML, OWL, SHACL, or similar schema modeling tools, and implement knowledge representations using RDF triples or labeled property graphs.
• Design and optimize entity resolution algorithms using techniques such as blocking strategies, embedding similarity, and rule-based matching.
• Develop ontology alignment techniques and graph embedding models such as Node2Vec or TransE-style approaches where appropriate.
• Design hybrid retrieval architectures combining dense vector retrieval, sparse retrieval techniques, and graph traversal algorithms such as BFS, DFS, path ranking, and neighborhood expansion.
• Build validation systems that enforce schema conformance, detect semantic inconsistencies, and reduce hallucinated or invalid structured outputs.
• Integrate structured knowledge systems into GraphRAG pipelines, agent planning frameworks, and tool-selection workflows.
• Deliver production-grade semantic systems with clear targets for latency, scalability, reliability, and data integrity.

Requirements

• 5+ years of experience building production AI or machine learning systems.
• Strong experience designing and implementing knowledge graphs or ontology-driven architectures.
• Hands-on experience implementing structured extraction techniques, including grammar-constrained decoding, JSON schema enforcement, or AST-style parsing approaches.
• Experience building entity resolution systems beyond simple embedding similarity methods.
• Experience working with graph query languages such as SPARQL or Cypher and optimizing graph query performance.
• Familiarity with RDF, OWL, or property graph data models and semantic data architectures.
• Strong Python engineering skills, with emphasis on data validation, schema integrity, and system reliability.
• Experience designing hybrid symbolic and neural AI systems.

Nice to Have:

• Experience implementing graph algorithms such as PageRank, community detection, or shortest-path algorithms for reasoning chains.
• Experience building graph-enhanced retrieval systems such as GraphRAG.
• Experience designing compositional semantic extraction pipelines.
• Experience implementing reasoning engines or rule-based inference systems.
• Experience benchmarking and evaluating structural extraction accuracy and consistency.

AuxoAI is hiring a Senior Applied Scientist to design and deploy production-grade AI agents capable of structured reasoning, planning, and decision-making.

This role focuses on building intelligent agent systems that combine LLM-based reasoning with classical planning, search algorithms, and optimization techniques. The ideal candidate will develop robust agent architectures that operate reliably in real-world environments with constraints around latency, cost, uncertainty, and limited context windows.

You will work on advanced AI systems that power autonomous workflows, decision engines, and tool-driven agent ecosystems.

You will work on problems where existing architectures may not be sufficient, and will be expected to experiment with new approaches that combine machine learning, graph algorithms, and classical AI techniques to build reliable, production-grade systems.

Location - Mumbai/Bangalore/Hyderabad/Gurgaon (Hybrid - 3 Days a week in Office)

Responsibilities:

• Design and architect modular AI agent frameworks incorporating skill decomposition, tool orchestration, and persistent state tracking.
• Implement planning and search algorithms such as Monte Carlo Tree Search (MCTS), beam search, A search, heuristic search, and graph-based planning approaches* to support complex decision-making tasks.
• Develop decision-making loops that balance trade-offs between exploration vs. exploitation, cost vs. accuracy, and latency vs. reasoning depth.
• Build structured memory systems including episodic memory stores, semantic memory layers, and vector-based memory with optimized retrieval strategies.
• Design tool-calling architectures with strong execution validation, retry mechanisms, and failure recovery strategies.
• Develop evaluation frameworks to measure agent performance using task success metrics, rollout simulations, and multi-sample validation approaches.
• Improve agent performance through techniques such as distillation, synthetic trajectory generation, prompt compression, and context pruning.
• Deliver production-ready agent systems that meet operational requirements around reliability, cost efficiency, throughput, and observability.

Requirements

• 2-5 years of experience building machine learning or AI systems in production environments.
• Strong experience implementing search or planning algorithms beyond basic use cases, including tree search or heuristic-based planning approaches.
• Hands-on experience with Monte Carlo Tree Search (MCTS) or related decision-making frameworks.
• Strong understanding of state-space representations, heuristic design, and decision boundary trade-offs.
• Experience building or extensively customizing agent frameworks for real-world applications.
• Hands-on experience designing tool-use or function-calling architectures under practical system constraints.
• Strong Python engineering skills with a focus on scalable and reliable system design.

Nice to Have:

• Experience with reinforcement learning techniques such as policy gradients, value estimation, or reward modeling.
• Experience building multi-agent or collaborative agent systems.
• Experience designing evaluation frameworks for agent robustness and reliability.
• Experience optimizing LLM inference pipelines for latency, throughput, and cost efficiency.
• Familiarity with distributed task orchestration systems and large-scale AI workflow management.