Ampera Technologies

Role Overview

We are seeking an experienced Power BI & Microsoft Fabric Consultant to partner with our BI team for a short-term engagement focused on capability building, governance setup, and platform enablement.

The primary objective of this role is to upskill the team and establish a robust, scalable foundation for Power BI and Microsoft Fabric—covering security, governance, administration, and best practices—so that the team can independently manage and scale the platform post-engagement.

This is a hands-on + coaching role, not just advisory.

Key Responsibilities

1. Power BI & Fabric Enablement

• Conduct structured training sessions and workshops on:
• Power BI (Pro + Fabric-integrated experiences)
• Microsoft Fabric (Lakehouse, Warehouse, Dataflows Gen2, Pipelines, etc.)
• Build foundational understanding of:
• End-to-end analytics workflows in Fabric
• Integration between Power BI and Fabric workloads 
• Data Lake will be Snowflake

2. Governance & Security Framework

• Design and implement Power BI & Fabric governance model, including:
• Workspace strategy (Dev/Test/Prod separation)
• Naming conventions and standards
• Content lifecycle management
• Establish security architecture:
• Role-based access control (RBAC)
• Row-Level Security (RLS) / Object-Level Security (OLS)
• Data access patterns across Fabric and Power BI
• Define data sharing and access control processes

3. Administration & Platform Setup

• Configure and optimize:
• Power BI tenant settings
• Fabric capacity (capacity planning, workload management)
• Monitoring and usage metrics
• Set up:
• Deployment pipelines
• CI/CD best practices (where applicable)
• Audit logs and governance controls

4. Best Practices & Standards

• Define and document:
• Development standards (data modeling, DAX, report design)
• Performance optimization guidelines
• Dataset/reusable semantic model strategy
• Establish certification and promotion workflows for datasets and reports

5. Hands-On Implementation

• Work alongside the team to:
• Build or refactor key dashboards/reports using best practices
• Set up Fabric artifacts (Lakehouse/Warehouse/Pipelines)
• Ensure real use cases are implemented, not just theoretical training

6. Knowledge Transfer & Self-Sufficiency

• Provide:
• Playbooks, SOPs, and governance documentation
• Recorded sessions and training materials
• Mentor team members through:
• Office hours / Q&A sessions
• Code and architecture reviews
• Ensure the team can independently:
• Manage Fabric capacity
• Govern Power BI environment
• Implement secure and scalable solutions

Expected Outcomes (End of Engagement)

• Fully defined and implemented Power BI & Fabric governance framework
• Configured and optimized Fabric capacity + Power BI tenant
• Established security and access control processes
• Documented standards, playbooks, and operating model
• BI team capable of independent development, administration, and governance

Required Skills & Experience

Must-Have

• 5+ years of experience in Power BI development and administration
• Hands-on experience with Microsoft Fabric (end-to-end)
• Strong expertise in:
• Power BI governance and tenant administration
• Fabric capacity management
• Security models (RLS, RBAC, data access controls)
• Experience setting up enterprise BI governance frameworks
• Proven track record of training and mentoring teams

Good-to-Have

• Experience with data platforms (Snowflake, Azure, etc.)
• Knowledge of CI/CD for Power BI (DevOps integration)
• Familiarity with data catalog and lineage tools (e.g., Atlan, Alation)
• Understanding of modern data architecture patterns

Job Description: Scrum Trainer / Agile Coach

Role Title:

Scrum Trainer / Agile Coach

Location: Chennai/Bangalore - Remote / On-site (as required)

Employment Type: Full-time / Contract

About the Role

We are looking for an experienced Scrum Trainer or Agile Coach who can enable teams to adopt Agile practices effectively. The role involves training, coaching, and mentoring teams to improve delivery, collaboration, and agility.

Key Responsibilities

• Conduct Scrum and Agile training sessions for teams and leadership
• Coach teams on Agile frameworks including Scrum, Kanban, and Lean
• Facilitate Agile ceremonies (Sprint Planning, Daily Stand-ups, Retrospectives, Reviews)
• Drive Agile transformation and mindset across teams
• Identify gaps and implement process improvements
• Mentor Scrum Masters and Product Owners
• Track Agile maturity and performance metrics

Required Skills & Experience

• 4+ years of experience in Agile / Scrum roles
• Strong understanding of Scrum framework and Agile principles
• Experience in conducting training and workshops
• Excellent facilitation, communication, and stakeholder management skills
• Hands-on experience with tools like Jira, Azure DevOps, etc.

Certifications (Preferred)

• Certified Scrum Master (CSM)
• Professional Scrum Master (PSM)
• SAFe Agilist or equivalent Agile certifications

Preferred Experience

• Experience working with cross-functional tech teams
• Exposure to Agile transformation in organizations
• Experience in coaching distributed teams

Storytelling Specialist (Freelancer – PowerPoint & Narrative Design)

Role Title:

Storytelling Specialist – Presentation Design (Freelance)

Location: Chennai/Bangalore / Project-based

Engagement Type: Freelancer / Contract

About the Role

We are looking for a creative storyteller who can transform ideas, data, and concepts into compelling PowerPoint presentations. The ideal candidate should be able to craft narratives that engage, simplify, and influence diverse audiences.

Key Responsibilities

• Convert raw content, data, and briefs into structured, impactful presentations
• Build strong storytelling flow (problem → insight → solution → impact)
• Design visually appealing and professional PowerPoint decks
• Collaborate with stakeholders to understand messaging and audience
• Simplify complex concepts into easy-to-understand visuals and narratives
• Ensure consistency in branding, tone, and communication

Required Skills & Experience

• Proven experience in presentation design and storytelling
• Strong expertise in Microsoft PowerPoint / Google Slides
• Ability to create narratives for business, social impact, or consulting contexts
• Good understanding of visual design principles (layout, typography, color)
• Strong communication and interpretation skills

Preferred Experience

• Experience working in consulting, startups, or social impact sectors
• Exposure to DEI, accessibility, or inclusion-related storytelling
• Basic knowledge of data visualization

Deliverables

• High-quality PowerPoint decks
• Storyboarding documents (if required)
• Visual templates and reusable formats

About the Role

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.

Key Responsibilities

·      Design, develop, and deploy machine learning models for real-world business problems

·      Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring

·      Implement and manage MLOps pipelines for scalable and reproducible workflows

·      Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management

·      Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications

·      Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions

·      Optimize model performance and ensure production stability

·      Stay updated with the latest advancements in AI/ML and GenAI ecosystems

Required Skills & Qualifications

·      4+ years of experience in Data Science / Machine Learning

·      Strong programming skills in Python

·      Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)

·      Solid understanding of MLOps practices and tools

·      Experience with MLflow or similar model lifecycle tools 

·      Practical experience in Generative AI (GenAI), including working with LLMs

·      Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch

·      Strong understanding of data structures, algorithms, and statistics

·      Experience with cloud platforms (AWS/GCP/Azure) is a plus

Good to Have

·      Experience with LLM fine-tuning, prompt engineering, or RAG pipelines

·      Exposure to Docker, Kubernetes, and CI/CD pipelines

·      Knowledge of data engineering workflows 

Job Description:

1.     Machine Learning Development & Deployment

·      Design and implement supervised and unsupervised models for predictive analytics, including churn prediction, demand forecasting, renewal risk scoring, and cross sell/upsell opportunity identification.

·      Translate business problems into ML frameworks and production solutions that improve efficiency, revenue, or customer experience.

·      Build, optimize, and maintain ML pipelines using tools such as MLflow, Airflow, or Kubeflow.

2.     Cross-Functional ML Use Cases

·      Partner with teams across Sales (e.g., lead scoring, next-best action), Customer Service (e.g., case deflection, sentiment analysis), Finance (e.g., revenue forecasting, fraud detection), Supply Chain (e.g., inventory optimization, ETA prediction), and Order Fulfillment (e.g., delivery risk modeling) to define impactful ML use cases.

·      Develop domain-specific models and continuously improve them using feedback loops and real-world performance data. 3.

3.      Model Governance and MLOps

·      Ensure robust model monitoring, versioning, and retraining strategies to keep models reliable in dynamic environments.

·      Work closely with DevOps and Data Engineering teams to automate deployment, CI/CD workflows, and cloud-native ML infrastructure (AWS/GCP/Azure).

4. Data Engineering and Feature Architecture

·      Collaborate with data engineers to define feature stores, data quality checks, and model-ready datasets on platforms like Snowflake or Databricks.

·      Perform feature selection, transformation, and engineering aligned with each domain’s business logic. 5. Communication & Stakeholder Collaboration

·      Present technical insights and model results to business and executive stakeholders in a clear, actionable format.

·      Work with Product Owners and Program Managers to scope, prioritize, and plan delivery of ML projects.

Qualifications:

Required

• Bachelor’s or Master’s degree in (e.g., Computer Science, Engineering, Statistics, Mathematics)

• 4+ years of experience in machine learning, data science.

• Proficiency in Python, XGBoost, PyTorch, TensorFlow, or similar.

• Experience deploying models into production using ML pipelines and orchestration frameworks.

• Strong understanding of data structures, SQL, and cloud platforms (e.g., AWS SageMaker, Azure ML, or GCP Vertex AI).

• Hands-on experience in implementing machine learning algorithms such as Random Forest, XGBoost, Logistic Regression, and Deep Learning techniques including Neural Networks (ANN, CNN)

Preferred:

• Experience supporting business functions such as Finance, Sales, or Operations with ML use cases.

• Familiarity with MLOps tools (MLflow, SageMaker Pipelines, Feature Store).

• Exposure to enterprise data platforms (e.g., Snowflake, Oracle Fusion, Salesforce).

• Background in statistics, forecasting, optimization, or recommendation systems.

Hi ,

We are looking for Oracle Incentive Compensation & Order Management Techno-Functional Consultant

PFB the Job Description:

Job Title: Oracle Incentive Compensation & Order Management Techno-Functional Consultant

Experience: 5+ Years

Location: Remote

Key Responsibilities

Oracle EBS & Incentive Compensation

• Design, configure, and implement Oracle Incentive Compensation (OIC) solutions within Oracle EBS R12.
• Analyze and integrate sales compensation plans, quota management, and commission calculations.
• Configure Plan Elements, Rate Tables, Compensation Plans, Pay Groups, and Sales Rep structures.
• Develop and enhance commission and incentive reporting frameworks.

Technical Development

• Develop PL/SQL packages, procedures, and functions for enterprise applications.
• Build RICEW components (Reports, Interfaces, Conversions, Extensions, Workflows).
• Create XML Publisher (BI Publisher) reports using RTF and XSLT templates.
• Develop and enhance custom workflows and concurrent programs.

Integration & Cloud Technologies

• Design and implement integration solutions using Oracle Integration Cloud (OIC).
• Develop REST web services using Oracle EBS Integrated SOA Gateway (ISG).
• Build integrations between Oracle EBS and external applications (Salesforce, ERP Cloud, third-party systems).
• Implement inbound and outbound interfaces for enterprise data exchange.

Implementation & Support

• Participate in full lifecycle implementations, upgrades, and system stabilization projects.
• Conduct requirements gathering, PRD preparation, and functional/technical design documentation.
• Perform unit testing, integration testing, and UAT support.
• Provide production support and issue resolution for business-critical applications.

Data Migration & Bulk Data Handling

• Use SQL*Loader, Export/Import utilities, and data loaders (FBDI, HCM DL) for large-scale data migration.
• Manage data conversion from legacy systems to Oracle EBS/Fusion applications.

Technical Skills

ERP & Cloud Platforms

• Oracle E-Business Suite R12
• Oracle Incentive Compensation (OIC / ICM)
• Oracle Fusion ERP Cloud (Finance & SCM)
• Oracle Integration Cloud (OIC)

Development Technologies

• PL/SQL
• SQL
• XML / XSLT
• REST Web Services

Tools & Utilities

• TOAD
• PL/SQL Developer
• SQL*Loader
• Oracle Forms 6i
• Oracle Reports 6i
• BI/XML Publisher

Databases

• Oracle 9i / 10g

Functional Knowledge

• CRM Foundation
• Core HR
• P2P, O2C cycles
• Order Management, Inventory, Purchasing

Job Description:

We are seeking a Cloud & AI Platform Engineer to design and operate AI-native infrastructure that supports large-scale machine learning, generative AI, and agentic AI systems. 

This role will focus on building secure, scalable, and automated multi-cloud platforms across AWS, Azure, GCP, and hybrid on-prem environments, enabling teams to deploy LLMs, AI agents, and data-driven applications reliably in production. 

You will work at the intersection of cloud engineering, MLOps, LLMOps, DevOps, and data infrastructure, helping build platforms that support RAG pipelines, vector search, AI model lifecycle management, and AI observability. 

Key Responsibilities

AI & Agentic Infrastructure 

• Design infrastructure to support agentic AI systems, autonomous agents, and multi-agent workflows. 
• Build scalable runtime environments for LLM orchestration frameworks. 
• Enable deployment of AI copilots, assistants, and autonomous decision systems. 

Common frameworks may include: 

• LangChain 
• LlamaIndex 
• AutoGPT 

LLMOps & AI Model Lifecycle 

Design and manage LLMOps pipelines for the full lifecycle of large language models: 

• Model deployment 
• Prompt management 
• Versioning 
• Evaluation and testing 
• Model monitoring 

Integrate with AI platforms such as: 

• Azure Machine Learning 
• Amazon SageMaker 
• Vertex AI 

Retrieval-Augmented Generation (RAG) Infrastructure 

Design and optimize RAG pipelines that integrate enterprise knowledge with LLMs. 

Responsibilities include: 

• Document ingestion pipelines 
• Embedding generation workflows 
• Knowledge indexing 
• Query orchestration 
• Retrieval optimization 
• Support scalable semantic search architectures. 

Vector Database & Knowledge Infrastructure 

Deploy and manage vector databases used for AI applications and semantic retrieval. 

Common technologies include: 

• Pinecone 
• Weaviate 
• Milvus 
• FAISS 

Responsibilities include: 

• Index optimization 
• Query latency tuning 
• Scalable embedding storage 
• Hybrid search architecture 

Multi-Cloud AI Infrastructure 

Design and maintain AI-ready infrastructure across: 

• Amazon Web Services 
• Microsoft Azure 
• Google Cloud Platform 

Key responsibilities include: 

• GPU infrastructure management 
• Distributed training environments 
• Hybrid cloud integrations with on-prem data centers 
• Infrastructure scaling for AI workloads 

Data Platforms & Integration 

• Support deployment and optimization of data lakes, data warehouses, and streaming platforms. 
• Work with data engineering teams to ensure secure and scalable data infrastructure. 

Cloud Architecture & Infrastructure 

• Design and implement scalable multi-cloud infrastructure across Azure, AWS, and Google Cloud. 
• Build hybrid cloud architectures integrating on-premise environments with cloud platforms. 
• Implement high availability, disaster recovery, and auto-scaling architectures for AI workloads. 

DevOps, Platform Engineering & Automation 

Build automated cloud infrastructure using modern DevOps practices. 

Tools may include: 

• Terraform 
• Docker 
• Kubernetes 
• GitHub Actions 

Responsibilities include: 

• Infrastructure as Code (IaC) 
• Automated deployments 
• CI/CD pipelines for AI models and services 
• Platform reliability and scalability 

AI Observability & Monitoring 

Implement observability frameworks to monitor AI systems in production. 

This includes: 

• Model performance monitoring 
• Prompt evaluation 
• Hallucination detection 
• Latency and throughput analysis 
• Cost monitoring for LLM usage 

Tools may include: 

• Arize AI 
• WhyLabs 
• Weights & Biases 

Security, Governance & Responsible AI 

Ensure AI systems follow strong governance and security practices. 

Responsibilities include: 

• Data privacy and compliance 
• Model governance frameworks 
• Secure model deployment 
• Monitoring model bias and drift 
• AI risk management 

Support enterprise frameworks for Responsible AI and AI compliance. 

Data & Security 

• Experience with data lake architectures, distributed storage, and ETL pipelines 
• Knowledge of data security, encryption, IAM, and compliance frameworks 
• Familiarity with AI governance and responsible AI practices 

Required Skills 

Cloud & Infrastructure 

• Strong experience in Azure (must have), AWS or GCP 
• Hybrid and multi-cloud architecture 
• GPU infrastructure management 

DevOps & Automation 

• Kubernetes 
• Docker 
• Terraform 
• CI/CD pipelines 

AI / ML Platforms 

• MLOps pipelines 
• Model deployment 
• Model monitoring 

AI Application Infrastructure 

• Vector databases 
• RAG pipelines 
• LLM orchestration frameworks 

Programming 

Experience in one or more languages: 

• Python 
• Go 
• Java 
• TypeScript 

Preferred Qualifications 

• Experience building AI copilots or autonomous agents 
• Knowledge of distributed model training - Knowledge of GPU infrastructure and distributed training 
• Familiarity with AI evaluation frameworks - Familiarity with model monitoring, drift detection, and AI observability 
• Experience building enterprise AI platforms 

Education & Experience 

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field 
• 4–8+ years experience in cloud infrastructure, DevOps, or platform engineering 
• Experience working in data-driven or AI-focused environments 

What Success Looks Like 

• Reliable ML model deployment pipelines - Reliable infrastructure for LLMs and AI agents, Scalable RAG knowledge platforms 
• Efficient multi-cloud infrastructure management - Fast deployment cycles for AI products 
• Secure and scalable AI-ready cloud platforms 
• Strong automation and governance across cloud and AI systems 

Job Description:

We are looking for a skilled Ethical Hacker (Penetration Tester) who will be responsible for identifying vulnerabilities in systems, networks, and applications before malicious hackers can exploit them. The role involves conducting security assessments, penetration testing, and recommending security improvements to strengthen the organization’s cybersecurity posture.

Key Responsibilities

·      Conduct penetration testing on web applications, mobile applications, APIs, and networks.

·      Identify security vulnerabilities and weaknesses in systems and infrastructure.

·      Perform vulnerability assessments using automated tools and manual techniques.

·      Simulate cyberattacks to evaluate the effectiveness of existing security measures.

·      Prepare detailed security reports highlighting risks, vulnerabilities, and remediation strategies.

·      Collaborate with development, DevOps, and IT teams to fix security gaps.

·      Ensure compliance with security standards and frameworks such as OWASP, ISO 27001, and NIST.

·      Conduct security audits and risk assessments across digital platforms.

·      Stay updated on the latest hacking techniques, security vulnerabilities, and cyber threats.

Required Skills & Qualifications

• Bachelor’s degree in Computer Science, Cybersecurity, Information Technology, or related field.
• 4+ years of experience in ethical hacking, penetration testing, or cybersecurity.
• Strong knowledge of network security, system security, and application security.
• Experience with security tools such as:
• Burp Suite
• Metasploit
• Nmap
• Wireshark
• Kali Linux
• Knowledge of OWASP Top 10 vulnerabilities.
• Understanding of Linux, Windows, and cloud security environments.
• Strong analytical and problem-solving skills.

Preferred Certifications

• CEH (Certified Ethical Hacker)
• OSCP (Offensive Security Certified Professional)
• CompTIA Security+
• CISSP (optional but valuable)

Key Competencies

• Cybersecurity risk assessment
• Vulnerability management
• Penetration testing methodologies
• Incident response awareness
• Strong documentation and reporting skills

Nice to Have

• Experience in cloud security (AWS, Azure, GCP)

Hi ,

Title                            : Senior AI/ML Engineer

Experience                 : 5 – 10+ Yrs

Location                     : Bengaluru

Work Type                : Hybrid – 2 days Work from office

Type of hire               : PwD & Non-PwD Inclusive Hiring

Employment Type     : Full Time

Notice Period             : Immediate Joiner

Workdays                   : Mon - Fri

Role Overview

We are seeking an exceptional AI Engineer who can design and build production-grade AI systems that combine advanced machine learning, Generative AI, and scalable software engineering.

This role goes beyond traditional data science and focuses on building end-to-end AI platforms, autonomous AI agents, intelligent decision systems, and enterprise AI applications.

You will work on real-world enterprise problems across industries, developing AI systems that automate reasoning, prediction, and decision-making at scale.

What You Will Build

Examples of systems you may work on:

• AI Copilots for enterprise workflows

• Autonomous AI agents for automation

• Decision intelligence platforms

• Retrieval-Augmented Generation (RAG) systems

• Predictive ML systems for forecasting and anomaly detection

• AI-powered knowledge assistants

• Intelligent automation platforms

Key Responsibilities

1. Advanced Machine Learning & Predictive Systems

Design and implement ML models including:

• Time series forecasting

• Predictive modeling

• Anomaly detection

• Recommendation systems

• NLP / text intelligence

• Deep learning models

Develop models using:

• PyTorch

• TensorFlow

• Scikit-learn

• XGBoost / LightGBM

2. Generative AI & LLM Systems

Build enterprise-grade GenAI applications including:

• AI copilots

• conversational agents

• document intelligence systems

• enterprise knowledge assistants

Develop LLM systems using:

• OpenAI / Claude / Gemini / Llama

• prompt engineering techniques

• embeddings and semantic search

• RAG architectures

3. Agentic AI Systems

Design autonomous AI systems capable of reasoning and executing tasks.

Build multi-agent architectures using:

• LangGraph

• CrewAI

• AutoGen

• Semantic Kernel

Integrate agents with:

• APIs

• enterprise data systems

• internal workflows

4. AI Platform Engineering

Develop scalable AI services and applications using:

• Python

• FastAPI / Flask

• asynchronous processing

• distributed compute frameworks

Build production-grade APIs and AI services.

5. Enterprise AI Deployment & MLOps

Deploy AI models into scalable production environments.

Work with:

• Docker

• Kubernetes

• CI/CD pipelines

• MLflow / experiment tracking

• model monitoring and drift detection

Deploy AI solutions on:

• Azure

• AWS

• GCP

6. Data Integration & AI Systems

Work with enterprise data sources including:

• relational databases

• data warehouses (Snowflake, Redshift, BigQuery)

• data lakes (S3 / Azure Data Lake)

• vector databases (Pinecone, Weaviate, FAISS)

Required Skills:

Programming

Expert-level proficiency in:

• Python

• software engineering best practices

• data structures and algorithms

Experience building production-ready systems.

Machine Learning

Strong expertise in:

• supervised learning

• unsupervised learning

• deep learning

• time-series modelling

• model evaluation and optimization

Generative AI

Experience working with:

• LLM APIs

• prompt engineering

• RAG pipelines

• embeddings and vector search

AI Architecture

Ability to design:

• scalable AI systems

• distributed ML systems

• intelligent automation platforms

Preferred Experience

• Building enterprise AI products

• Developing AI copilots or agents

• Designing decision intelligence platforms

• Experience with large-scale data systems

Ideal Candidate Profile

The ideal candidate is:

• A strong ML engineer AND software engineer

• Comfortable building AI systems end-to-end

• Experienced in deploying models to production

• Passionate about next-generation AI architectures

We value builders who ship real systems, not just research prototypes.

Education

Bachelor’s / Master’s in:

Computer Science

Artificial Intelligence

Machine Learning

Data Science

or related field.

Why Join Ampera

At Ampera, we are building AI-native enterprise platforms that transform how organizations use data and intelligence.

Engineers at Ampera work on:

• real-world enterprise AI systems

• cutting-edge GenAI and agentic architectures

• global enterprise clients across industries

• high-impact AI platforms that scale.

What Makes This Role Unique

You will help build the next generation of enterprise AI systems — where AI moves beyond prediction and becomes an autonomous decision-making layer for organizations.

About Ampera:

Ampera Technologies, a purpose driven Digital IT Services with primary focus on supporting our client with their Data, AI / ML, Accessibility and other Digital IT needs. We also ensure that equal opportunities are provided to Persons with Disabilities Talent. Ampera Technologies has its Global Headquarters in Chicago, USA and its Global Delivery Center is based out of Chennai, India. We are actively expanding our Tech Delivery team in Chennai and across India. We offer exciting benefits for our teams, such as 1) Hybrid and Remote work options available, 2) Opportunity to work directly with our Global Enterprise Clients, 3) Opportunity to learn and implement evolving Technologies, 4) Comprehensive healthcare, and 5) Conducive environment for Persons with Disability Talent meeting Physical and Digital Accessibility standards

Accessibility & Inclusion Statement

We are committed to creating an inclusive environment for all employees, including persons with disabilities. Reasonable accommodations will be provided upon request.

Equal Opportunity Employer (EOE) Statement

Ampera Technologies is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

.

About Ampera

Ampera builds enterprise-grade AI platforms that sit at the intersection of large-scale data systems, intelligent orchestration, and applied AI.

Our products help Fortune 1000 companies optimize operations, manage risk, and unlock decision intelligence using AI, LLMs, and agentic workflows.

Role Overview

We are looking for a strong Full Stack Engineer who has built production-grade enterprise applications, worked with large datasets, and is excited about integrating AI systems and LLM-powered workflows into real-world platforms.

This is not a UI-only or API-only role.

You’ll own end-to-end system design, from frontend experiences to backend orchestration and AI integration.

What You’ll Work On

• Enterprise web platforms used by analysts, admins, and leadership
• High-scale data-intensive applications (query orchestration, risk intelligence, estimation engines)
• AI-augmented workflows (LLMs, agents, optimizers, explainability layers)
• Secure, governed, multi-tenant systems with role-based access

Key Responsibilities

Full Stack Development

• Design and build scalable web applications (frontend + backend)
• Develop API-first backend services for enterprise workflows
• Build admin dashboards, analyst workflows, and decision-ready UIs
• Ensure performance, reliability, and maintainability at scale

Backend & Data Systems

• Work with large-scale relational databases (Azure Synapse, Redshift, Snowflake, PostgreSQL, SQL Server, etc.)
• Design data models for high-volume, analytical workloads
• Implement caching, orchestration, background processing, and async workflows
• Integrate with enterprise systems (identity, BI tools, data platforms)

AI / LLM Integration

• Integrate LLMs (OpenAI, Azure OpenAI, etc.) into production systems
• Build AI-powered services:
• Query optimization
• Risk scoring & explainability
• Estimation & prediction workflows
• Implement agentic AI patterns (multi-step reasoning, tool-using agents, orchestration)
• Work closely with ML engineers to productionize AI models

Enterprise Readiness

• Implement RBAC, audit logging, governance, and guardrails
• Design systems with security, compliance, and observability in mind
• Contribute to CI/CD pipelines, deployments, and production monitoring

Required Skills & Experience

Core Engineering

• 4–8+ years of experience as a Full Stack Engineer
• Strong backend experience with Python (FastAPI preferred) or equivalent
• Solid frontend experience with React / modern JS frameworks
• Strong understanding of REST APIs, async processing, microservices

Data & Systems

• Hands-on experience with large databases and complex schemas
• Strong SQL skills and experience optimizing queries
• Experience building enterprise-grade, data-heavy applications

AI / Modern Stack

• Practical experience integrating LLMs or AI services into applications
• Familiarity with:
• Prompting & structured outputs
• AI evaluation & guardrails
• Explainability and risk-aware AI
• Exposure to agentic AI frameworks or multi-step AI workflows is a big plus

Nice-to-Have (Strong Differentiators)

• Experience building AI-powered SaaS or internal enterprise platforms
• Background in analytics, risk systems, finance, supply chain, or operations
• Experience with Redis, message queues, background workers
• Familiarity with Azure / AWS, containerization, Kubernetes
• Ability to translate business problems → system design

What We Look For (Beyond Skills)

• Strong systems thinking — you see the whole picture
• Comfortable operating in ambiguous, zero-to-one builds
• Ability to reason about scale, cost, and enterprise constraints
• Builder mindset — you ship, iterate, and own outcomes

Why Join Ampera

• Work on real enterprise AI platforms, not demos or chatbots
• Exposure to LLMs, agentic AI, and applied AI at scale
• High ownership, senior-heavy team, minimal bureaucracy
• Opportunity to shape core architecture and AI strategy
•