Impacto Digifin Technologies
https://impactodigifin.comAbout
Impacto Digifin Technologies empowers businesses to embrace digital transformation with intelligent, AI-driven solutions. Our platforms simplify document management, data verification, and compliance processes, reducing manual effort, enhancing accuracy, and accelerating results. From fast-growing fintechs to established enterprises, our solutions are designed to adapt to unique operational needs, whether it’s streamlining customer onboarding, automating back-office workflows, or eliminating paperwork bottlenecks.
What sets Impacto Digifin apart is our hybrid approach—leveraging automation for speed while maintaining human oversight where it matters most. This ensures efficiency without compromising trust, enabling organizations to operate with clarity and control. More than just a technology provider, we act as a digital partner, helping teams scale smarter, optimize processes, and transform their operations with confidence.
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Impacto Digifin Technologies provides AI-powered solutions that streamline document management, data verification, and compliance for businesses.
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Jobs at Impacto Digifin Technologies
Job Title: Project Manager (BFSI) – Full Time
Experience: 2+ Years
Location: Brookefield, Bangalore Urban, Karnataka
Engagement Type: Full Time (Monday to Saturday, 9 AM to 6 PM)
Description
The Project Manager (BFSI) – Full Time role is responsible for managing and delivering IT projects within the Banking, Financial Services, and Insurance (BFSI) sector. The role requires strong project governance, execution discipline, and a solid understanding of BFSI operational and regulatory frameworks. You will oversee end-to-end project delivery while coordinating stakeholders, ensuring compliance, and maintaining high-quality outcomes.
Responsibilities
Lead and execute BFSI-focused IT projects from initiation to closure.
Develop and manage the project scope, timelines, resource plans, and budgets.
Coordinate cross-functional teams and vendors to ensure successful project execution.
Maintain clear communication with stakeholders, providing updates on risks, issues, and milestones.
Conduct project reviews, stand-ups, and status meetings to drive alignment.
Prepare documentation such as project plans, risk registers, and compliance reports.
Ensure adherence to organizational standards and BFSI regulatory requirements.
Implement corrective actions proactively to maintain delivery quality and timelines.
Requirements
Minimum 3+ years of experience in IT project management, preferably within the BFSI domain.
Proven track record of delivering IT projects within defined schedules and budgets.
Good understanding of BFSI compliance, operational processes, and technology environments.
Proficiency in project methodologies and tools (Agile, Waterfall, JIRA, MS Project, etc.).
Strong interpersonal, communication, problem-solving, and stakeholder management skills.
Ability to work independently and manage multiple tasks in a fast-paced environment.
Project management certifications (PMP, Prince2, Agile) are advantageous.
Python
Machine Learning (ML)
Deep LearningAbout Impacto Digifin Technologies
Impacto Digifin Technologies enables enterprises to adopt digital transformation through intelligent, AI-powered solutions. Our platforms reduce manual work, improve accuracy, automate complex workflows, and ensure compliance—empowering organizations to operate with speed, clarity, and confidence.
We combine automation where it’s fastest with human oversight where it matters most. This hybrid approach ensures trust, reliability, and measurable efficiency across fintech and enterprise operations.
Role Overview
We are looking for an AI Engineer Voice with strong applied experience in machine learning, deep learning, NLP, GenAI, and full-stack voice AI systems.
This role requires someone who can design, build, deploy, and optimize end-to-end voice AI pipelines, including speech-to-text, text-to-speech, real-time streaming voice interactions, voice-enabled AI applications, and voice-to-LLM integrations.
You will work across core ML/DL systems, voice models, predictive analytics, banking-domain AI applications, and emerging AGI-aligned frameworks. The ideal candidate is an applied engineer with strong fundamentals, the ability to prototype quickly, and the maturity to contribute to R&D when needed.
This role is collaborative, cross-functional, and hands-on.
Key Responsibilities
Voice AI Engineering
- Build end-to-end voice AI systems, including STT, TTS, VAD, audio processing, and conversational voice pipelines.
- Implement real-time voice pipelines involving streaming interactions with LLMs and AI agents.
- Design and integrate voice calling workflows, bi-directional audio streaming, and voice-based user interactions.
- Develop voice-enabled applications, voice chat systems, and voice-to-AI integrations for enterprise workflows.
- Build and optimize audio preprocessing layers (noise reduction, segmentation, normalization)
- Implement voice understanding modules, speech intent extraction, and context tracking.
Machine Learning & Deep Learning
- Build, deploy, and optimize ML and DL models for prediction, classification, and automation use cases.
- Train and fine-tune neural networks for text, speech, and multimodal tasks.
- Build traditional ML systems where needed (statistical, rule-based, hybrid systems).
- Perform feature engineering, model evaluation, retraining, and continuous learning cycles.
NLP, LLMs & GenAI
- Implement NLP pipelines including tokenization, NER, intent, embeddings, and semantic classification.
- Work with LLM architectures for text + voice workflows
- Build GenAI-based workflows and integrate models into production systems.
- Implement RAG pipelines and agent-based systems for complex automation.
Fintech & Banking AI
- Work on AI-driven features related to banking, financial risk, compliance automation, fraud patterns, and customer intelligence.
- Understand fintech data structures and constraints while designing AI models.
Engineering, Deployment & Collaboration
- Deploy models on cloud or on-prem (AWS / Azure / GCP / internal infra).
- Build robust APIs and services for voice and ML-based functionalities.
- Collaborate with data engineers, backend developers, and business teams to deliver end-to-end AI solutions.
- Document systems and contribute to internal knowledge bases and R&D.
Security & Compliance
- Follow fundamental best practices for AI security, access control, and safe data handling.
- Awareness of financial compliance standards (plus, not mandatory).
- Follow internal guidelines on PII, audio data, and model privacy.
Primary Skills (Must-Have)
Core AI
- Machine Learning fundamentals
- Deep Learning architectures
- NLP pipelines and transformers
- LLM usage and integration
- GenAI development
- Voice AI (STT, TTS, VAD, real-time pipelines)
- Audio processing fundamentals
- Model building, tuning, and retraining
- RAG systems
- AI Agents (orchestration, multi-step reasoning)
Voice Engineering
- End-to-end voice application development
- Voice calling & telephony integration (framework-agnostic)
- Realtime STT ↔ LLM ↔ TTS interactive flows
- Voice chat system development
- Voice-to-AI model integration for automation
Fintech/Banking Awareness
- High-level understanding of fintech and banking AI use cases
- Data patterns in core banking analytics (advantageous)
Programming & Engineering
- Python (strong competency)
- Cloud deployment understanding (AWS/Azure/GCP)
- API development
- Data processing & pipeline creation
Secondary Skills (Good to Have)
- MLOps & CI/CD for ML systems
- Vector databases
- Prompt engineering
- Model monitoring & evaluation frameworks
- Microservices experience
- Basic UI integration understanding for voice/chat
- Research reading & benchmarking ability
Qualifications
- 2–3 years of practical experience in AI/ML/DL engineering.
- Bachelor’s/Master’s degree in CS, AI, Data Science, or related fields.
- Proven hands-on experience building ML/DL/voice pipelines.
- Experience in fintech or data-intensive domains preferred.
Soft Skills
- Clear communication and requirement understanding
- Curiosity and research mindset
- Self-driven problem solving
- Ability to collaborate cross-functionally
- Strong ownership and delivery discipline
- Ability to explain complex AI concepts simply
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